100+ datasets found
  1. Thyroid Disease Data

    • kaggle.com
    zip
    Updated Jun 9, 2022
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    Emmanuel F. Werr (2022). Thyroid Disease Data [Dataset]. https://www.kaggle.com/datasets/emmanuelfwerr/thyroid-disease-data
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    zip(148814 bytes)Available download formats
    Dataset updated
    Jun 9, 2022
    Authors
    Emmanuel F. Werr
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    The datasets featured below were created by reconciling thyroid disease datasets provided by the UCI Machine Learning Repository.

    Content

    The size for the file featured within this Kaggle dataset is shown below — along with a list of attributes, and their description summaries: - thyroidDF.csv - 9172 observations x 31 attributes

    1. age - age of the patient (int)
    2. sex - sex patient identifies (str)
    3. on_thyroxine - whether patient is on thyroxine (bool)
    4. query on thyroxine - *whether patient is on thyroxine (bool)
    5. on antithyroid meds - whether patient is on antithyroid meds (bool)
    6. sick - whether patient is sick (bool)
    7. pregnant - whether patient is pregnant (bool)
    8. thyroid_surgery - whether patient has undergone thyroid surgery (bool)
    9. I131_treatment - whether patient is undergoing I131 treatment (bool)
    10. query_hypothyroid - whether patient believes they have hypothyroid (bool)
    11. query_hyperthyroid - whether patient believes they have hyperthyroid (bool)
    12. lithium - whether patient * lithium (bool)
    13. goitre - whether patient has goitre (bool)
    14. tumor - whether patient has tumor (bool)
    15. hypopituitary - whether patient * hyperpituitary gland (float)
    16. psych - whether patient * psych (bool)
    17. TSH_measured - whether TSH was measured in the blood (bool)
    18. TSH - TSH level in blood from lab work (float)
    19. T3_measured - whether T3 was measured in the blood (bool)
    20. T3 - T3 level in blood from lab work (float)
    21. TT4_measured - whether TT4 was measured in the blood (bool)
    22. TT4 - TT4 level in blood from lab work (float)
    23. T4U_measured - whether T4U was measured in the blood (bool)
    24. T4U - T4U level in blood from lab work (float)
    25. FTI_measured - whether FTI was measured in the blood (bool)
    26. FTI - FTI level in blood from lab work (float)
    27. TBG_measured - whether TBG was measured in the blood (bool)
    28. TBG - TBG level in blood from lab work (float)
    29. referral_source - (str)
    30. target - hyperthyroidism medical diagnosis (str)
    31. patient_id - unique id of the patient (str)

    Target Metadata

      The diagnosis consists of a string of letters indicating diagnosed conditions.
      A diagnosis "-" indicates no condition requiring comment. A diagnosis of the
      form "X|Y" is interpreted as "consistent with X, but more likely Y". The
      conditions are divided into groups where each group corresponds to a class of
      comments.
    
      Letter Diagnosis
      ------ ---------
    
      hyperthyroid conditions:
    
      A  hyperthyroid
      B  T3 toxic
      C  toxic goitre
      D  secondary toxic
    
      hypothyroid conditions:
    
      E  hypothyroid
      F  primary hypothyroid
      G  compensated hypothyroid
      H  secondary hypothyroid
    
      binding protein:
    
      I  increased binding protein
      J  decreased binding protein
    
      general health:
    
      K  concurrent non-thyroidal illness
    
      replacement therapy:
    
      L  consistent with replacement therapy
      M  underreplaced
      N  overreplaced
    
      antithyroid treatment:
    
      O  antithyroid drugs
      P  I131 treatment
      Q  surgery
    
      miscellaneous:
    
      R  discordant assay results
      S  elevated TBG
      T  elevated thyroid hormones
    

    Source

    Thyroid Data - https://archive.ics.uci.edu/ml/datasets/thyroid+disease

  2. Thyroid Disease Dataset

    • kaggle.com
    zip
    Updated Jun 4, 2025
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    Sikandar AiDev (2025). Thyroid Disease Dataset [Dataset]. https://www.kaggle.com/datasets/sikandaraidev/thyroid-dataset
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    zip(126874 bytes)Available download formats
    Dataset updated
    Jun 4, 2025
    Authors
    Sikandar AiDev
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    This dataset is a cleaned, transformed, and research-informed version of the original Thyroid Disease records compiled by the Garavan Institute and J. Ross Quinlan (1984–1987). It contains 9,000+ patient records with lab values, clinical history, and diagnosis outcomes. All missing values (?) were removed, and redundant or conflicting entries were dropped.

    The dataset is valuable for Healthcare and Medical Research focused on thyroid-related Health Conditions. It supports Multiclass Classification problems in Artificial Intelligence and Data Analytics, particularly within Computer Science and Healthcare domains.

    Missing values have been removed and categorical flags (t/f) converted to boolean (True/False). Meaningful multiclass target labels were created based on clinical diagnosis codes, including handling ambiguous cases. Data types were adjusted for compatibility with machine learning workflows using tools like pandas, NumPy, and scikit-learn.

    This dataset is suitable for users of all skill levels—Beginner, Intermediate, and Advanced—interested in exploring Classification, Feature Extraction, Data Cleaning, and Exploratory Data Analysis in healthcare datasets. Visualizations can be developed using Matplotlib and Seaborn to better understand thyroid disease patterns.

    Boolean fields (t/f) were converted to True/False, and a meaningful target variable was created based on clinically grounded groupings described in the research article “Thyroid Disease Prediction Using Selective Features and Machine Learning Techniques” (PMCID: PMC9405591).

    The original diagnosis strings (e.g., A|B) were resolved to reflect the most likely class, and diagnoses were mapped into simplified, interpretable categories suitable for classification tasks (e.g., hypothyroid, hyperthyroid, normal, etc.).

    This version is optimized for machine learning applications such as:

    • Classification of thyroid status (e.g., binary or multi-class)

    • Feature selection and model evaluation

    • Clinical decision support research

    • Ideal for healthcare ML projects, educational purposes, and benchmarking thyroid disorder prediction models.

  3. Data_Sheet_1_Overall, sex-and race/ethnicity-specific prevalence of thyroid...

    • frontiersin.figshare.com
    docx
    Updated Jun 20, 2024
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    Jianzhou Chen; Lingling Zhang; Xiaowen Zhang (2024). Data_Sheet_1_Overall, sex-and race/ethnicity-specific prevalence of thyroid dysfunction in US adolescents aged 12–18 years.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2024.1366485.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Jianzhou Chen; Lingling Zhang; Xiaowen Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    BackgroundThyroid dysfunction significantly affects the health and development of adolescents. However, comprehensive studies on its prevalence and characteristics in US adolescents are lacking.MethodsWe investigated the prevalence of thyroid dysfunction in US adolescents aged 12–18 years using data from the National Health and Nutrition Examination Survey (NHANES) 2001–2002 and 2007–2012 cycles. Thyroid dysfunction was assessed using serum thyroid-stimulating hormone (TSH) and free thyroxine (fT4) measurements. We analyzed the prevalence across demographic subgroups and identified associated risk factors.ResultsThe study included 2,182 participants, representing an estimated 12.97 million adolescents. The group had a weighted mean age of 15.1 ± 0.06 years, with males constituting 51.4%. Subclinical hyperthyroidism emerged as the most prevalent thyroid dysfunction, affecting 4.4% of the population. From 2001–2002 to 2011–2012, subclinical hyperthyroidism remained consistent at 4.99% vs. 5.13% in the overall cohort. Subclinical and overt hypothyroidism was found in 0.41 and 1.03% of adolescents respectively, and overt hyperthyroidism was rare (0.04%). The prevalence of thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb) positivity in the overall population were 5.8 and 9.8%, respectively. Positivity for TgAb was risk factors for hypothyroidism, while older age, female and Black Americans were risk factors for hyperthyroidism. Female adolescents and adolescents with an older age were more likely to be positive for TPOAb and TgAb, while Black and Mexican Americans had a lower risk of TPOAb and TgAb positivity.ConclusionSubclinical hyperthyroidism was the most common form of thyroid dysfunction, and its prevalence remained stable from 2001–2002 to 2011–2012. Notable disparities in the prevalence of hyperthyroidism and antibody positivity were observed among different age, sex and racial/ethnic groups.

  4. f

    Table_1_Causal associations between thyroid dysfunction and COVID-19...

    • datasetcatalog.nlm.nih.gov
    Updated Sep 6, 2022
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    Lv, Yonggang; Zhang, Zhihao; Fang, Tian (2022). Table_1_Causal associations between thyroid dysfunction and COVID-19 susceptibility and severity: A bidirectional Mendelian randomization study.xlsx [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000389214
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    Dataset updated
    Sep 6, 2022
    Authors
    Lv, Yonggang; Zhang, Zhihao; Fang, Tian
    Description

    BackgroundObservational studies have reported an association between coronavirus disease 2019 (COVID-19) risk and thyroid dysfunction, but without a clear causal relationship. We attempted to evaluate the association between thyroid function and COVID-19 risk using a bidirectional two-sample Mendelian randomization (MR) analysis.MethodsSummary statistics on the characteristics of thyroid dysfunction (hypothyroidism and hyperthyroidism) were obtained from the ThyroidOmics Consortium. Genome-wide association study statistics for COVID-19 susceptibility and its severity were obtained from the COVID-19 Host Genetics Initiative, and severity phenotypes included hospitalization and very severe disease in COVID-19 participants. The inverse variance-weighted (IVW) method was used as the primary analysis method, supplemented by the weighted-median (WM), MR-Egger, and MR-PRESSO methods. Results were adjusted for Bonferroni correction thresholds.ResultsThe forward MR estimates show no effect of thyroid dysfunction on COVID-19 susceptibility and severity. The reverse MR found that COVID-19 susceptibility was the suggestive risk factor for hypothyroidism (IVW: OR = 1.577, 95% CI = 1.065–2.333, P = 0.022; WM: OR = 1.527, 95% CI = 1.042–2.240, P = 0.029), and there was lightly association between COVID-19 hospitalized and hypothyroidism (IVW: OR = 1.151, 95% CI = 1.004–1.319, P = 0.042; WM: OR = 1.197, 95% CI = 1.023-1.401, P = 0.023). There was no evidence supporting the association between any phenotype of COVID-19 and hyperthyroidism.ConclusionOur results identified that COVID-19 might be the potential risk factor for hypothyroidism. Therefore, patients infected with SARS-CoV-2 should strengthen the monitoring of thyroid function.

  5. f

    Data from: Primary headache subtypes and thyroid dysfunction: Is there any...

    • datasetcatalog.nlm.nih.gov
    • scielo.figshare.com
    Updated Mar 24, 2021
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    BOUGEA, Anastasia; ANAGNOSTOU, Evangelos; KARARIZOU, Evangelia; RIZONAKI, Konstantina; LIAKAKIS, Georgios; CHRISTIDI, Foteini; SPANOU, Ioanna (2021). Primary headache subtypes and thyroid dysfunction: Is there any association? [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000861065
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    Dataset updated
    Mar 24, 2021
    Authors
    BOUGEA, Anastasia; ANAGNOSTOU, Evangelos; KARARIZOU, Evangelia; RIZONAKI, Konstantina; LIAKAKIS, Georgios; CHRISTIDI, Foteini; SPANOU, Ioanna
    Description

    ABSTRACT Background: Primary headaches, and particularly migraine and tension-type headache (TTH) as well as hypothyroidism are common medical conditions. To date, numerous studies have suggested a possible bidirectional relationship between migraine and hypothyroidism, although certain studies had contradictory results. Objective: To investigate whether there is any association between primary headache subtypes and thyroid disorders. Methods: A retrospective study of consecutive patients aged ≥18 years referred to the Headache Outpatient Clinic of Aeginition Hospital and diagnosed with primary headache and any thyroid disorder. Results: Out of 427 patients (males/females=76/351), 253 (59.3%) were diagnosed with migraine without aura, 53 (12.4%) with TTH, 49 (11.5%) with migraine with aura, 29 (6.8%) with medication-overuse headache, 23 (5.4%) with mixed-type headache (migraine with/without aura and TTH), nine (2.1%) with cluster headache, and 11 (2.6%) with other types of primary headaches. The prevalence of any type of thyroid disorder was 20.8% (89/427 patients). In the total sample, 27 patients (6.3%) reported hypothyroidism, 18 (4.2%) unspecified thyroidopathy, 14 (3.3%) thyroid nodules, 12 (2.8%) Hashimoto thyroiditis, 12 (2.8%) thyroidectomy, three (0.7%) thyroid goiter, and three (0.7%) hyperthyroidism. Further statistical analysis between categorical variables did not reveal any significant association between headache subtypes and thyroid dysfunction. Conclusions: No specific association was found between primary headache subtypes and specific thyroid disorder. However, a high prevalence of thyroid dysfunction in general and specifically hypothyroidism was demonstrated among patients with primary headaches, which lays the foundation for further clarification in prospective longitudinal studies.

  6. Share of people with thyroid problems India 2021, by age group

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Share of people with thyroid problems India 2021, by age group [Dataset]. https://www.statista.com/statistics/1123549/india-share-of-respondents-with-thyroid-issues-by-age-group/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    India
    Description

    As per the results of a large scale survey conducted across India in 2021, about ** percent of the respondents above 60 years of age suffered from thyroid problems. Whereas around **** percent of the respondents below 19 years of age reported to have thyroid issues.

  7. c

    Thyroid Disorder Therapy Market - Price, Size, Share & Growth

    • coherentmarketinsights.com
    Updated Nov 24, 2025
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    Coherent Market Insights (2025). Thyroid Disorder Therapy Market - Price, Size, Share & Growth [Dataset]. https://www.coherentmarketinsights.com/market-insight/thyroid-disorder-therapy-market-2687
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    Dataset updated
    Nov 24, 2025
    Dataset authored and provided by
    Coherent Market Insights
    License

    https://www.coherentmarketinsights.com/privacy-policyhttps://www.coherentmarketinsights.com/privacy-policy

    Time period covered
    2025 - 2031
    Area covered
    Global
    Description

    Thyroid Disorder Therapy Market is segmented By Disease Type (Thyroid Cancer, Hypothyroidism, goiter and Hyperthyroidism) and Drug Class (Levothyroxine, Liothyronine, Kinase Inhibitors, Anthracyclines and Beta-Blockers)

  8. f

    Data from: Initial evaluation of thyroid dysfunction - Are simultaneous TSH...

    • datasetcatalog.nlm.nih.gov
    Updated Apr 30, 2018
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    Bremner, Alexandra P.; Aujesky, Drahomir; Collet, Tinh-Hai; Feddema, Peter; Peeters, Robin P.; Schneider, Claudio; O’Leary, Peter C.; Bauer, Douglas C.; Leedman, Peter J.; Feller, Martin; Rodondi, Nicolas; da Costa, Bruno R.; Brown, Suzanne J.; Auer, Reto; Walsh, John P. (2018). Initial evaluation of thyroid dysfunction - Are simultaneous TSH and fT4 tests necessary? [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000617985
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    Dataset updated
    Apr 30, 2018
    Authors
    Bremner, Alexandra P.; Aujesky, Drahomir; Collet, Tinh-Hai; Feddema, Peter; Peeters, Robin P.; Schneider, Claudio; O’Leary, Peter C.; Bauer, Douglas C.; Leedman, Peter J.; Feller, Martin; Rodondi, Nicolas; da Costa, Bruno R.; Brown, Suzanne J.; Auer, Reto; Walsh, John P.
    Description

    ObjectiveGuidelines for thyroid function evaluation recommend testing TSH first, then assessing fT4 only if TSH is out of the reference range (two-step), but many clinicians initially request both TSH and fT4 (one-step). Given limitations of previous studies, we aimed to compare the two-step with the one-step approach in an unselected community-dwelling study population, and develop a prediction score based on clinical parameters that could identify at-risk patients for thyroid dysfunction.DesignCross-sectional analysis of the population-based Busselton Health Study.MethodsWe compared the two-step with the one-step approach, focusing on cases that would be missed by the two-step approach, i.e. those with normal TSH, but out-of-range fT4. We used likelihood ratio tests to identify demographic and clinical parameters associated with thyroid dysfunction and developed a clinical prediction score by using a beta-coefficient based scoring method.ResultsFollowing the two-step approach, 93.0% of all 4471 participants had normal TSH and would not need further testing. The two-step approach would have missed 3.8% of all participants (169 of 4471) with a normal TSH, but a fT4 outside the reference range. In 85% (144 of 169) of these cases, fT4 fell within 2 pmol/l of fT4 reference range limits, consistent with healthy outliers. The clinical prediction score that performed best excluded only 22.5% of participants from TSH testing.ConclusionThe two-step approach may avoid measuring fT4 in as many as 93% of individuals with a very small risk of missing thyroid dysfunction. Our findings do not support the simultaneous initial measurement of both TSH and fT4.

  9. Prevalence of thyroid disorder in Italy 2016-2022

    • statista.com
    Updated Nov 26, 2025
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    Statista (2025). Prevalence of thyroid disorder in Italy 2016-2022 [Dataset]. https://www.statista.com/statistics/937054/prevalence-of-thyroid-diseases-in-italy/
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    Dataset updated
    Nov 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Italy
    Description

    The estimated prevalence of thyroid disorder increased in Italy from 2016 to 2022. In 2016, around ** percent of the Italian clients of general practitioners suffered from thyroid disorders. In 2021 and 2022, the prevalence of this disorder in Italy was **** percent, the highest figure registered in the period under consideration. This statistic displays the prevalence of thyroid disorder in Italy from 2016 to 2022.

  10. m

    Thyroid Gland Disorders Treatment Market Forecasts 2030

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Jan 30, 2025
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    Mordor Intelligence (2025). Thyroid Gland Disorders Treatment Market Forecasts 2030 [Dataset]. https://www.mordorintelligence.com/industry-reports/thyroid-gland-disorders-treatment-market
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    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jan 30, 2025
    Dataset authored and provided by
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2019 - 2030
    Area covered
    Global
    Description

    The Thyroid Gland Disorders Treatment Market report segments the industry into By Type Of Disorder (Hypothyroidism, Hyperthyroidism, Other Types Of Disorder), By Route Of Administration (Oral, Parenteral, Other Routes Of Administration), By Drug Class (Thioamides, Ionic Inhibitors, Hormone-release Inhibitors, Other Drug Classes), By Distribution Channel (Wholesale Distribution, Retail Stores, and more), and Geography.

  11. DataSheet2_The Causal Effects of Primary Biliary Cholangitis on Thyroid...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 8, 2023
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    Peng Huang; Yuqing Hou; Yixin Zou; Xiangyu Ye; Rongbin Yu; Sheng Yang (2023). DataSheet2_The Causal Effects of Primary Biliary Cholangitis on Thyroid Dysfunction: A Two-Sample Mendelian Randomization Study.xlsx [Dataset]. http://doi.org/10.3389/fgene.2021.791778.s002
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    xlsxAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Peng Huang; Yuqing Hou; Yixin Zou; Xiangyu Ye; Rongbin Yu; Sheng Yang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Background: Primary biliary cholangitis (PBC) is an autoimmune disease and is often accompanied by thyroid dysfunction. Understanding the potential causal relationship between PBC and thyroid dysfunction is helpful to explore the pathogenesis of PBC and to develop strategies for the prevention and treatment of PBC and its complications.Methods: We used a two-sample Mendelian randomization (MR) method to estimate the potential causal effect of PBC on the risk of autoimmune thyroid disease (AITD), thyroid-stimulating hormone (TSH) and free thyroxine (FT4), hyperthyroidism, hypothyroidism, and thyroid cancer (TC) in the European population. We collected seven datasets of PBC and related traits to perform a series MR analysis and performed extensive sensitivity analyses to ensure the reliability of our results.Results: Using a sensitivity analysis, we found that PBC was a risk factor for AITD, TSH, hypothyroidism, and TC with odds ratio (OR) of 1.002 (95% CI: 1.000–1.005, p = 0.042), 1.016 (95% CI: 1.006–1.027, p = 0.002), 1.068 (95% CI: 1.022–1.115, p = 0.003), and 1.106 (95% CI: 1.019–1.120, p = 0.042), respectively. Interestingly, using reverse-direction MR analysis, we also found that AITD had a significant potential causal association with PBC with an OR of 0.021 (p = 5.10E−4) and that the other two had no significant causal relation on PBC.Conclusion: PBC causes thyroid dysfunction, specifically as AITD, mild hypothyroidism, and TC. The potential causal relationship between PBC and thyroid dysfunction provides a new direction for the etiology of PBC.

  12. Data from: Thyroid Disease Detection DataSet

    • kaggle.com
    zip
    Updated May 27, 2024
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    Amir Mohammad Parvizi (2024). Thyroid Disease Detection DataSet [Dataset]. https://www.kaggle.com/datasets/amirmohammadparvizi/thyroid-disease-detection-dataset
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    zip(148814 bytes)Available download formats
    Dataset updated
    May 27, 2024
    Authors
    Amir Mohammad Parvizi
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Amir Mohammad Parvizi

    Released under MIT

    Contents

  13. Data from: Gender, race and socioeconomic influence on diagnosis and...

    • scielo.figshare.com
    • search.datacite.org
    jpeg
    Updated May 31, 2023
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    R.D. Olmos; R.C. de Figueiredo; E.M. Aquino; P.A. Lotufo; I.M. Bensenor (2023). Gender, race and socioeconomic influence on diagnosis and treatment of thyroid disorders in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) [Dataset]. http://doi.org/10.6084/m9.figshare.7899950.v1
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    jpegAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    SciELOhttp://www.scielo.org/
    Authors
    R.D. Olmos; R.C. de Figueiredo; E.M. Aquino; P.A. Lotufo; I.M. Bensenor
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Thyroid diseases are common, and use of levothyroxine is increasing worldwide. We investigated the influence of gender, race and socioeconomic status on the diagnosis and treatment of thyroid disorders using data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), a multicenter cohort study of civil servants (35-74 years of age) from six Brazilian cities. Diagnosis of thyroid dysfunction was by thyrotropin (TSH), and free thyroxine (FT4) if TSH was altered, and the use of specific medications. Multivariate logistic regression models were constructed using overt hyperthyroidism/hypothyroidism and levothyroxine use as dependent variables and sociodemographic characteristics as independent variables. The frequencies of overt hyper- and hypothyroidism were 0.7 and 7.4%, respectively. Using whites as the reference ethnicity, brown, and black race were protective for overt hypothyroidism (OR=0.76, 95%CI=0.64-0.89, and OR=0.53, 95%CI=0.43-0.67, respectively, and black race was associated with overt hyperthyroidism (OR=1.82, 95%CI=1.06-3.11). Frequency of hypothyroidism treatment was higher in women, browns, highly educated participants and those with high net family incomes. After multivariate adjustment, levothyroxine use was associated with female gender (OR=6.06, 95%CI=3.19-11.49) and high net family income (OR=3.23, 95%CI=1.02-10.23). Frequency of hyperthyroidism treatment was higher in older than in younger individuals. Sociodemographic factors strongly influenced the diagnosis and treatment of thyroid disorders, including the use of levothyroxine.

  14. c

    The global Thyroid Functioning Tests market size will be USD 4968.5 million...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Apr 4, 2025
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    Cognitive Market Research (2025). The global Thyroid Functioning Tests market size will be USD 4968.5 million in 2025. [Dataset]. https://www.cognitivemarketresearch.com/thyroid-functioning-tests-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Apr 4, 2025
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2022 - 2034
    Area covered
    Global
    Description

    According to Cognitive Market Research, the global Thyroid Functioning Tests market size will be USD 4968.5 million in 2025. It will expand at a compound annual growth rate (CAGR) of 7.00% from 2025 to 2033.

    North America held the major market share for more than 40% of the global revenue with a market size of USD 1838.35 million in 2025 and will grow at a compound annual growth rate (CAGR) of 5.8% from 2025 to 2033.
    Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1440.8 million.
    APAC held a market share of around 23% of the global revenue with a market size of USD 1192.4 million in 2025 and will grow at a compound annual growth rate (CAGR) of 9.6% from 2025 to 2033.
    South America has a market share of more than 5% of the global revenue with a market size of USD 188.80 million in 2025 and will grow at a compound annual growth rate (CAGR) of 7.3% from 2025 to 2033.
    Middle East had a market share of around 2% of the global revenue and was estimated at a market size of USD 198.74 million in 2025 and will grow at a compound annual growth rate (CAGR) of 7.5% from 2025 to 2033.
    Africa had a market share of around 1% of the global revenue and was estimated at a market size of USD 109.31 million in 2025 and will grow at a compound annual growth rate (CAGR) of 6.7% from 2025 to 2033.
    Power Filters category is the fastest growing segment of the Thyroid Functioning Tests industry
    

    Market Dynamics of Thyroid Functioning Tests Market

    Key Drivers for Thyroid Functioning Tests Market

    Rising Prevalence of Thyroid Disorders to Boost Market Growth

    Hypothyroidism and hyperthyroidism are becoming increasingly prevalent worldwide due to factors such as genetics, lifestyle changes, and environmental influences. Over 12 percent of the U.S. population will develop a thyroid condition at some point in their lives, and an estimated 20 million Americans currently have some form of thyroid disease. However, up to 60 percent of those with thyroid conditions are unaware of their diagnosis. Women are more likely to experience thyroid issues, with the risk being five to eight times higher than that of men. In fact, one in eight women will develop a thyroid disorder during their lifetime. These conditions can have a significant impact on metabolism and overall health, contributing to a growing demand for thyroid function tests. Additionally, autoimmune diseases, such as Hashimoto's thyroiditis (a common cause of hypothyroidism) and Graves' disease (which causes hyperthyroidism), are becoming more prevalent, further increasing the need for regular screening. As the global population ages, the likelihood of developing thyroid disorders, particularly hypothyroidism, also rises. This aging demographic requires more routine testing to monitor and manage thyroid health.

    https://www.thyroid.org/media-main/press-room//./

    Rise in Lifestyle-related Risk Factors to Boost Market Growth

    Increasing stress, poor diet, lack of physical activity, and environmental pollution are major risk factors for thyroid disorders. Approximately 284 million people worldwide suffer from anxiety disorders, and nearly 90% of U.S. adults report losing sleep due to concerns about health and the economy. Additionally, about 75% of Americans experience physical or mental symptoms of stress, with more than three-quarters of adults reporting issues such as headaches, fatigue, and depression. These lifestyle changes are contributing to a higher incidence of thyroid-related problems, which is driving the growing demand for thyroid function tests. Furthermore, exposure to chemicals and toxins in the environment, including those found in certain pesticides, has been linked to thyroid dysfunction, further increasing the need for regular monitoring.

    https://www.singlecare.com/blog/news/stress-statistics/./

    Restraint Factor for the Thyroid Functioning Tests Market

    High Cost of Advanced Diagnostic Tests and Challenges in Test Accuracy and Standardization, Will Limit Market Growth

    The cost of diagnostic equipment for thyroid function tests, such as automated analyzers and high-quality reagents, can be prohibitively expensive, especially for small clinics and healthcare facilities in emerging markets. Additionally, testing at high-end laboratories or through advanced diagnostic platforms often comes with higher costs, which may discourage patients from undergoing regular testing. Th...

  15. f

    Table 1_Analysis of independent risk factors and construction of a...

    • figshare.com
    docx
    Updated Nov 14, 2025
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    Yiliminuer Keremu; Xiaolu Yu; Gang Zhao; Xu Chen; Liang Wang; Yan Zhang; Fan Guo; Xiumin Ma (2025). Table 1_Analysis of independent risk factors and construction of a predictive model for thyroid dysfunction in early pregnancy.docx [Dataset]. http://doi.org/10.3389/fendo.2025.1631445.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Nov 14, 2025
    Dataset provided by
    Frontiers
    Authors
    Yiliminuer Keremu; Xiaolu Yu; Gang Zhao; Xu Chen; Liang Wang; Yan Zhang; Fan Guo; Xiumin Ma
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionThyroid dysfunction during early pregnancy significantly impacts maternal and fetal health, with risks including preeclampsia, preterm birth, and developmental abnormalities. This study aims to identify independent risk factors and develop a predictive model to enable early diagnosis and intervention, improving pregnancy outcomes through tailored clinical management strategies.MethodsWe retrospectively analyzed the general information and relevant laboratory indicators of 2151 women in early pregnancy admitted to three Xinjiang hospitals from April 2021 to November 2024. The patients were divided into a normal thyroid function group (n=1490) and a thyroid dysfunction group (n=661). The test results were analyzed to screen for independent risk factors and constructed a predictive model.ResultsKey findings revealed a 30.73% thyroid dysfunction incidence, including subclinical hypothyroidism (76.40%), hypothyroidism (12.86%), hyperthyroidism (6.35%), and subclinical hyperthyroidism (4.39%). Regional reference ranges were established as TSH (0.22–2.40) mIU/L and FT4 (13.54–20.26) pmol/L. Univariate analysis identified significant differences in A-TPO, A-TG, TSH, and FT3 (P

  16. Z

    Thyroid Gland Disorder Treatment Market By Disease Type (Hypothyroidism,...

    • zionmarketresearch.com
    pdf
    Updated Jan 14, 2026
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    Zion Market Research (2026). Thyroid Gland Disorder Treatment Market By Disease Type (Hypothyroidism, Hyperthyroidism), By Drug Type (Liothyronine, Levothyroxine, Imidazole, Propacil, Others), And By Region - Global And Regional Industry Overview, Market Intelligence, Comprehensive Analysis, Historical Data, And Forecasts 2024 - 2032 [Dataset]. https://www.zionmarketresearch.com/report/thyroid-gland-disorder-treatment-market
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jan 14, 2026
    Dataset authored and provided by
    Zion Market Research
    License

    https://www.zionmarketresearch.com/privacy-policyhttps://www.zionmarketresearch.com/privacy-policy

    Time period covered
    2022 - 2030
    Area covered
    Global
    Description

    Global Thyroid Gland Disorder Treatment Market size was worth around USD 2.42 billion in 2023 and is grow to around USD 3.17 billion by 2032 with a CAGR of 3.18%.

  17. H

    Ovarian function measures in normogonadotropic anovulation and subclinical...

    • datasetcatalog.nlm.nih.gov
    • search.dataone.org
    Updated Sep 1, 2024
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    Gawron, Iwona (2024). Ovarian function measures in normogonadotropic anovulation and subclinical thyroid dysfunction [Dataset]. http://doi.org/10.7910/DVN/ZFSUOO
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    Dataset updated
    Sep 1, 2024
    Authors
    Gawron, Iwona
    Description

    Ovarian function measures in normogonadotropic anovulation and subclinical hypothyroidism or thyroid autoimmunity

  18. G

    Thyroid Support Supplements Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 29, 2025
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    Growth Market Reports (2025). Thyroid Support Supplements Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/thyroid-support-supplements-market
    Explore at:
    pdf, pptx, csvAvailable download formats
    Dataset updated
    Aug 29, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Thyroid Support Supplements Market Outlook



    According to our latest research, the global thyroid support supplements market size reached USD 2.13 billion in 2024, demonstrating robust demand driven by increasing awareness of thyroid health and preventive wellness trends. The market is expected to grow at a CAGR of 7.1% from 2025 to 2033, with the total market value projected to reach USD 4.00 billion by 2033. This sustained growth is attributed to the rising prevalence of thyroid disorders, growing consumer inclination towards dietary supplements, and the expansion of digital health commerce platforms, as per our latest research findings.




    One of the primary growth factors propelling the thyroid support supplements market is the increasing incidence of thyroid-related disorders globally. Conditions such as hypothyroidism, hyperthyroidism, HashimotoÂ’s thyroiditis, and GravesÂ’ disease have seen a notable rise, particularly among adult and elderly populations. This trend is further exacerbated by lifestyle changes, environmental factors, and dietary deficiencies, especially iodine and selenium, which are critical for optimal thyroid function. As a result, consumers are proactively seeking thyroid support supplements as a preventive measure or as an adjunct to prescribed therapies. The growing public awareness, fueled by educational campaigns and healthcare professional recommendations, has significantly boosted the adoption of these supplements across various demographics.




    Another significant driver is the shift in consumer behavior towards preventive healthcare and wellness, which has become increasingly prominent in both developed and emerging markets. With the proliferation of information through digital media and health influencers, consumers are more informed about the importance of maintaining thyroid health and the potential long-term impacts of thyroid dysfunction. This has led to greater demand for natural and holistic products, with a marked preference for supplements containing herbal extracts, vitamins, minerals, and amino acids. The surge in online retailing and e-pharmacy platforms has further facilitated easy access to a wide range of thyroid support supplements, enabling consumers to compare, research, and purchase products tailored to their specific needs, thereby fueling market expansion.




    Technological advancements in supplement formulation and delivery systems also play a crucial role in market growth. Manufacturers are leveraging innovative encapsulation technologies, improved bioavailability, and novel combinations of active ingredients to enhance the efficacy of thyroid support supplements. These advancements not only improve consumer trust and compliance but also encourage repeat purchases. Additionally, regulatory bodies in key markets are increasingly recognizing and standardizing supplement quality, which boosts consumer confidence in product safety and effectiveness. The competitive landscape is thus characterized by continuous product innovation, strategic partnerships, and aggressive marketing strategies, all of which collectively drive the upward trajectory of the thyroid support supplements market.



    In addressing thyroid gland disorder treatment, it's crucial to consider both conventional and alternative approaches. Conventional treatments often involve hormone replacement therapy, which can effectively manage symptoms of hypothyroidism or hyperthyroidism. However, there is a growing interest in integrative therapies that combine traditional medicine with dietary and lifestyle interventions. These may include the use of specific nutrients, such as iodine and selenium, which are vital for thyroid function, as well as stress management techniques and herbal remedies. Such comprehensive treatment plans aim to not only alleviate symptoms but also address underlying causes, promoting overall endocrine health and wellness.




    From a regional perspective, North America continues to dominate the thyroid support supplements market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The high prevalence of thyroid disorders, coupled with well-established healthcare infrastructure and a strong culture of dietary supplementation, underpins the market's strength in these regions. Meanwhile, Asia Pacific is emerging as the fastest-gro

  19. f

    Data_Sheet_1_Abnormal Cardiac Repolarization in Thyroid Diseases: Results of...

    • datasetcatalog.nlm.nih.gov
    Updated Nov 23, 2021
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    Dietrich, Johannes Wolfgang Christian; Schöne, Dominik; Gotzmann, Michael; Akin, Ibrahim; El-Battrawy, Ibrahim; Mügge, Andreas; Bogossian, Harilaos; Landgrafe-Mende, Gabi; Patsalis, Polykarpos C.; Schiedat, Fabian; Aweimer, Assem (2021). Data_Sheet_1_Abnormal Cardiac Repolarization in Thyroid Diseases: Results of an Observational Study.docx [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000872722
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    Dataset updated
    Nov 23, 2021
    Authors
    Dietrich, Johannes Wolfgang Christian; Schöne, Dominik; Gotzmann, Michael; Akin, Ibrahim; El-Battrawy, Ibrahim; Mügge, Andreas; Bogossian, Harilaos; Landgrafe-Mende, Gabi; Patsalis, Polykarpos C.; Schiedat, Fabian; Aweimer, Assem
    Description

    Background: The relationship between thyroid function and cardiac disease is complex. Both hypothyroidism and thyrotoxicosis can predispose to ventricular arrhythmia and other major adverse cardiovascular events (MACE), so that a U-shaped relationship between thyroid signaling and the incidence of MACE has been postulated. Moreover, recently published data suggest an association between thyroid hormone concentration and the risk of sudden cardiac death (SCD) even in euthyroid populations with high-normal FT4 levels. In this study, we investigated markers of repolarization in ECGs, as predictors of cardiovascular events, in patients with a spectrum of subclinical and overt thyroid dysfunction.Methods: Resting ECGs of 100 subjects, 90 patients (LV-EF > 45%) with thyroid disease (60 overt hyperthyroid, 11 overt hypothyroid and 19 L-T4-treated and biochemically euthyroid patients after thyroidectomy or with autoimmune thyroiditis) and 10 healthy volunteers were analyzed for Tp-e interval. The Tp-e interval was measured manually and was correlated to serum concentrations of thyroid stimulating hormone (TSH), free triiodothyronine (FT3) and thyroxine (FT4).Results: The Tp-e interval significantly correlated to log-transformed concentrations of TSH (Spearman's rho = 0.30, p < 0.01), FT4 (rho = −0.26, p < 0.05), and FT3 (rho = −0.23, p < 0.05) as well as log-transformed thyroid's secretory capacity (SPINA-GT, rho = −0.33, p < 0.01). Spearman's rho of correlations of JT interval to log-transformed TSH, FT4, FT3, and SPINA-GT were 0.51 (p < 1e−7), −0.45 (p < 1e−5), −0.55 (p < 1e−8), and −0.43 (p < 1e−4), respectively. In minimal multivariable regression models, markers of thyroid homeostasis correlated to heart rate, QT, Tp-e, and JT intervals. Group-wise evaluation in hypothyroid, euthyroid and hyperthyroid subjects revealed similar correlations in all three groups.Conclusion: We observed significant inverse correlations of Tp-e and JT intervals with FT4 and FT3 over the whole spectrum of thyroid function. Our data suggest a possible mechanism of SCD in hypothyroid state by prolongation of repolarization. We do not observe a U-shaped relationship, so that the mechanism of SCD in patients with high FT4 or hyperthyroidism seems not to be driven by abnormalities in repolarization.

  20. T

    Thyroid Disorder Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Oct 6, 2025
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    Data Insights Market (2025). Thyroid Disorder Report [Dataset]. https://www.datainsightsmarket.com/reports/thyroid-disorder-1200142
    Explore at:
    pdf, doc, pptAvailable download formats
    Dataset updated
    Oct 6, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2026 - 2034
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Explore the booming Thyroid Disorder market, projected to reach USD 23.99 billion by 2033 with an 8.5% CAGR. Discover key drivers, trends, and regional insights for hypothyroidism and hyperthyroidism treatments.

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Emmanuel F. Werr (2022). Thyroid Disease Data [Dataset]. https://www.kaggle.com/datasets/emmanuelfwerr/thyroid-disease-data
Organization logo

Thyroid Disease Data

Patient demographics and blood test results along Thyroid Disease diagnostic

Explore at:
9 scholarly articles cite this dataset (View in Google Scholar)
zip(148814 bytes)Available download formats
Dataset updated
Jun 9, 2022
Authors
Emmanuel F. Werr
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

Context

The datasets featured below were created by reconciling thyroid disease datasets provided by the UCI Machine Learning Repository.

Content

The size for the file featured within this Kaggle dataset is shown below — along with a list of attributes, and their description summaries: - thyroidDF.csv - 9172 observations x 31 attributes

  1. age - age of the patient (int)
  2. sex - sex patient identifies (str)
  3. on_thyroxine - whether patient is on thyroxine (bool)
  4. query on thyroxine - *whether patient is on thyroxine (bool)
  5. on antithyroid meds - whether patient is on antithyroid meds (bool)
  6. sick - whether patient is sick (bool)
  7. pregnant - whether patient is pregnant (bool)
  8. thyroid_surgery - whether patient has undergone thyroid surgery (bool)
  9. I131_treatment - whether patient is undergoing I131 treatment (bool)
  10. query_hypothyroid - whether patient believes they have hypothyroid (bool)
  11. query_hyperthyroid - whether patient believes they have hyperthyroid (bool)
  12. lithium - whether patient * lithium (bool)
  13. goitre - whether patient has goitre (bool)
  14. tumor - whether patient has tumor (bool)
  15. hypopituitary - whether patient * hyperpituitary gland (float)
  16. psych - whether patient * psych (bool)
  17. TSH_measured - whether TSH was measured in the blood (bool)
  18. TSH - TSH level in blood from lab work (float)
  19. T3_measured - whether T3 was measured in the blood (bool)
  20. T3 - T3 level in blood from lab work (float)
  21. TT4_measured - whether TT4 was measured in the blood (bool)
  22. TT4 - TT4 level in blood from lab work (float)
  23. T4U_measured - whether T4U was measured in the blood (bool)
  24. T4U - T4U level in blood from lab work (float)
  25. FTI_measured - whether FTI was measured in the blood (bool)
  26. FTI - FTI level in blood from lab work (float)
  27. TBG_measured - whether TBG was measured in the blood (bool)
  28. TBG - TBG level in blood from lab work (float)
  29. referral_source - (str)
  30. target - hyperthyroidism medical diagnosis (str)
  31. patient_id - unique id of the patient (str)

Target Metadata

  The diagnosis consists of a string of letters indicating diagnosed conditions.
  A diagnosis "-" indicates no condition requiring comment. A diagnosis of the
  form "X|Y" is interpreted as "consistent with X, but more likely Y". The
  conditions are divided into groups where each group corresponds to a class of
  comments.

  Letter Diagnosis
  ------ ---------

  hyperthyroid conditions:

  A  hyperthyroid
  B  T3 toxic
  C  toxic goitre
  D  secondary toxic

  hypothyroid conditions:

  E  hypothyroid
  F  primary hypothyroid
  G  compensated hypothyroid
  H  secondary hypothyroid

  binding protein:

  I  increased binding protein
  J  decreased binding protein

  general health:

  K  concurrent non-thyroidal illness

  replacement therapy:

  L  consistent with replacement therapy
  M  underreplaced
  N  overreplaced

  antithyroid treatment:

  O  antithyroid drugs
  P  I131 treatment
  Q  surgery

  miscellaneous:

  R  discordant assay results
  S  elevated TBG
  T  elevated thyroid hormones

Source

Thyroid Data - https://archive.ics.uci.edu/ml/datasets/thyroid+disease

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