From 2018 to 2022, the overall death rate for lung and bronchus cancer in the Kentucky was 61 per 100,000 for males and 43.2 per 100,000 for females. This statistic presents the death rates for lung and bronchus cancer in the United States from 2018 to 2022, by state and gender.

This dataset contains data about lung cancer Mortality and is a comprehensive collection of patient information, specifically focused on individuals diagnosed with cancer.

Description of columns:

• id: A unique identifier for each patient in the dataset.
• age: The age of the patient at the time of diagnosis.
• gender: The gender of the patient (e.g., male, female).
• country: The country or region where the patient resides.
• diagnosis_date: The date on which the patient was diagnosed with lung cancer.
• cancer_stage: The stage of lung cancer at the time of diagnosis (e.g., Stage I, Stage II, Stage III, Stage IV).
• family_history: Indicates whether there is a family history of cancer (e.g., yes, no).
• smoking_status: The smoking status of the patient (e.g., current smoker, former smoker, never smoked, passive smoker).
• bmi: The Body Mass Index of the patient at the time of diagnosis.
• cholesterol_level: The cholesterol level of the patient (value).
• hypertension: Indicates whether the patient has hypertension (high blood pressure) (e.g., yes, no).
• asthma: Indicates whether the patient has asthma (e.g., yes, no).
• cirrhosis: Indicates whether the patient has cirrhosis of the liver (e.g., yes, no).
• other_cancer: Indicates whether the patient has had any other type of cancer in addition to the primary diagnosis (e.g., yes, no).
• treatment_type: The type of treatment the patient received (e.g., surgery, chemotherapy, radiation, combined).
• end_treatment_date: The date on which the patient completed their cancer treatment or died.
• survived: Indicates whether the patient survived (e.g., yes, no).

File Information

A single CSV file containing 890000 rows and 17 columns of patient data.

In 2022, the mortality rate of lung cancer in the European was **** per 100,000 men and **** per 100,000 women. Among men the mortality rate was highest in Hungary and lowest in Sweden being *** and **** per 100,000 respectively. Hungary was also the country with the highest lung cancer mortality rate in women with **** per 100,000 women. The lowest was in Lithuania with **** per 100,000 women. In most EU countries, there was a marked difference between the mortality of lung cancer in men and women.

Lung Cancer Deaths reports the number, crude rate, and age-adjusted mortality rate (AAMR) of deaths due to lung cancer.

Lung Cancer Dataset

Introduction:

Lung cancer remains one of the most prevalent and deadly forms of cancer worldwide, posing significant challenges for early detection and effective treatment. To contribute to the global effort in understanding and combating this disease, we are excited to introduce our comprehensive Lung Cancer Dataset, now available on Kaggle.

Scientific Overview:

This dataset is an invaluable asset in the realm of Health Care, providing a structured foundation for the development of cancer detection models. This dataset exemplifies the variety of symptoms of Lung Cancer. Each category within the dataset—'GENDER', 'AGE', 'SMOKING', 'YELLOW_FINGERS', 'ANXIETY', 'PEER_PRESSURE', 'CHRONIC_DISEASE', 'FATIGUE', 'ALLERGY', 'WHEEZING', 'ALCOHOL_CONSUMING', 'COUGHING', 'SHORTNESS_OF_BREATH', 'SWALLOWING_DIFFICULTY', 'CHEST_PAIN'—has been carefully curated to encompass a diverse range of symptoms, ensuring that the resulting models are versatile and accurate. This scientific approach not only enhances the dataset's diversity to record symptoms of lung cancer but also contributes to the broader field of AI-driven health technologies, pushing the boundaries of what health care assistants can achieve.

Dataset Composition

The Lung Cancer Dataset includes a diverse array of symptoms essential for comprehensive analysis and model development. The primary categories of data are as follows:

1. Patient Demographics

Age: Provides the age at diagnosis, enabling analysis of age-related incidence and outcomes. Gender: Includes information on patient gender, facilitating gender-based studies. Smoking Status: Categorized as current smoker, former smoker, or non-smoker, this data is critical for evaluating the impact of smoking on lung cancer risk and progression.

2. Medical History

Comorbidities: Details additional health issues such as chronic obstructive pulmonary disease (COPD), which are relevant for treatment planning and prognosis.

3. Clinical Data

Vital Signs: Records of blood pressure, heart rate, respiratory rate, and other vital signs at diagnosis and during treatment.

Implementation Guide for the Mental Health Dataset:

Data Integration

Dataset Acquisition: Obtain the Lung Cancer Dataset. Data Exploration: Familiarize yourself with the structure and contents of the dataset, including symptoms and conclusions related to different conditions.

Preprocessing

Data Cleaning: Remove any irrelevant or redundant entries, and ensure consistency in formatting across the dataset. Tokenization: Break down the symptoms and conclusions into tokens or individual words to facilitate analysis and model training. Normalization: Standardize the text data by converting it to lowercase and removing punctuation or special characters as needed.

Model Training

Choose a Framework: Select a suitable machine learning or natural language processing framework such as TensorFlow, PyTorch, or spaCy. Model Selection: Decide on the type of model to use, such as recurrent neural networks (RNNs), transformers, or sequence-to-sequence models, based on the complexity of the dataset and the desired level of accuracy. Training Process: Train the chosen model using the preprocessed dataset, adjusting hyperparameters as necessary to optimize performance. Evaluation: Assess the performance of the trained model using appropriate metrics such as accuracy, precision, recall, and F1-score.

Deployment

Integration: Integrate the trained model into a chatbot or virtual assistant application using programming languages like Python or JavaScript. User Interface Design: Design an intuitive user interface that allows users to interact with the chatbot and receive responses related to Lung Cancer. Testing: Conduct thorough testing of the deployed chatbot to ensure functionality, accuracy, and responsiveness in providing relevant result. Feedback Mechanism: Implement a feedback mechanism to gather user feedback and improve the chatbot's performance over time.

Continuous Improvement

Monitoring: Continuously monitor the chatbot's performance and user interactions to identify areas for improvement. Data Updates: Periodically update the dataset with new symptoms to ensure accuracy. Model Refinement: Fine-tune the model based on user feedback and additional training data to enhance the chatbot's effectiveness and accuracy in detecting lung cancer. By following this implementation guide, developers can effectively leverage the Lung Cancer Dataset to build and deploy AI-driven chatbots and virtual assistants that offer accurate predictions to users worldwide.

Potential Applications

The extensive nature of the Lung Cancer Dataset supports a wide range of scientific and clinical applications:

Machine Learning Models: Facilitates the development of predictive algorithms for early detection, prognosis, and personalized t...

Death rate has been age-adjusted by the 2000 U.S. standard population. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Lung cancer is a leading cause of cancer-related death in the US. People who smoke have the greatest risk of lung cancer, though lung cancer can also occur in people who have never smoked. Most cases are due to long-term tobacco smoking or exposure to secondhand tobacco smoke. Cities and communities can take an active role in curbing tobacco use and reducing lung cancer by adopting policies to regulate tobacco retail; reducing exposure to secondhand smoke in outdoor public spaces, such as parks, restaurants, or in multi-unit housing; and improving access to tobacco cessation programs and other preventive services.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Legacy unique identifier: P00508

Mortality from lung cancer (ICD-10 C33-C34 equivalent to ICD-9 162). To reduce deaths from lung cancer. Legacy unique identifier: P00508

This statistic shows the death rate of lung and bronchus cancer in the United States from 1999 to 2023. The maximum rate in the given period was **** per every 100,000 age-adjusted population in 2000. The minimum rate stood at **** in 2023.

Deaths from lung cancer - Directly age-Standardised Rates (DSR) per 100,000 population Source: Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Primary Care Trust (PCT), Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2005-07, 2007 Type of data: Administrative data

In 2020, approximately ** men and ** women per 100,000 population died from lung cancer in England and Wales. During the provided time interval, there has been a noticeable decrease in the mortality of lung cancer among men, while the rate among women has remained at similar levels since the year 2000.

Rate: Number of deaths due to cancer of the trachea, bronchus, and lung per 100,000 Population.

Definition: Number of deaths per 100,000 with malignant neoplasm (cancer) cancer of the trachea, bronchus, and lung as the underlying cause (ICD-10 codes: C33-C34).

Data Sources:

(1) Centers for Disease Control and Prevention, National Center for Health Statistics. Compressed Mortality File. CDC WONDER On-line Database accessed at http://wonder.cdc.gov/cmf-icd10.html

(2) Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health

(3) Population Estimates, State Data Center, New Jersey Department of Labor and Workforce Development

Abstract Objective: To identify the socioepidemiologic and histopathologic patterns of lung cancer patients in the Middle Euphrates region. Patients and Methods: This study analyzed medical information from lung cancer patients at the Middle Euphrates Cancer Center in Iraq from January 2018 to December 2023. Demographic information (age, gender, residency, and education level) as well as clinical details (histopathological categorization) were obtained. The inclusion criteria included all confirmed lung cancer cases, while cases with inadequate data or non-lung cancer diagnosis were omitted. The data were analyzed using IBM SPSS Statistics (version 26). The data summarized using descriptive statistics, and chi-square tests used to identify correlations between categorical variables at a significance level of p < 0.05. Ethical approval was obtained from the relevant institutional review board. Results: A total of 1162 patients were included with mean age at diagnosis(64.47±11.45) years. Majority of patients are over 60 years (64.4%), followed by (40–60 years), 34%, and the least affected group is under 40 years (1.6%). Males account for the majority of cases (68%), while females about 32%, with male:female ratio that fluctuate around 2:1. Illiterate patients and those with low education levels represent the largest proportion accounting for about 87.9% of the study population. Squamous Cell Carcinoma (SCC) is the most frequent subtype (41.7%), followed closely by Adenocarcinoma (AC) at 37%, and Small Cell Lung Cancer (SCLC), 10.5%. Although SCC is the predominant subtype overall, AC incidence is increasing overtime (from 31.7% in 2018 to 41.4% in 2023) with predominance in females, younger and higher educated groups. While the percentage of SCLC and other less common subgroups remained relatively stable over time, there is a significant reduction in NSCLC-NOS diagnoses (from 11.1% in 2018 to 3.2% in 2023). Conclusions: In Iraq, specifically in the Middle Euphrates region, lung cancer is a major public health issue in the elder age groups. The two main subtypes, SCC and AC, are the main contributors, with obvious increment in AC cases in the recent years. The shifting trends indicate the urgent need for improved screening strategies, focused preventative initiatives, and customized treatment plans in view of changing risk profiles.

In 2020, the mortality rate for lung cancer was **** per 100,000 population among males in Canada. This statistic displays the age-standardized mortality rate of lung cancers among males in Canada between 1988 and 2020, with forecasts from 2021 to 2023.

The effectiveness of cancer prediction system helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status. The data is collected from the website online lung cancer prediction system . **Total no. of attributes: **16 No .of instances: 284 **Attribute information: ** Gender: M(male), F(female) Age: Age of the patient Smoking: YES=2 , NO=1. Yellow fingers: YES=2 , NO=1. Anxiety: YES=2 , NO=1. Peer_pressure: YES=2 , NO=1. Chronic Disease: YES=2 , NO=1. Fatigue: YES=2 , NO=1. Allergy: YES=2 , NO=1. Wheezing: YES=2 , NO=1. Alcohol: YES=2 , NO=1. Coughing: YES=2 , NO=1. Shortness of Breath: YES=2 , NO=1. Swallowing Difficulty: YES=2 , NO=1. Chest pain: YES=2 , NO=1. Lung Cancer: YES , NO.

Dataset Description This dataset contains information on cancer deaths by country, type, and year. It includes data on 18 different types of cancer, including liver cancer, kidney cancer, larynx cancer, breast cancer, thyroid cancer, stomach cancer, bladder cancer, uterine cancer, ovarian cancer, cervical cancer, prostate cancer, pancreatic cancer, esophageal cancer, testicular cancer, nasopharynx cancer, other pharynx cancer, colon and rectum cancer, non-melanoma skin cancer, lip and oral cavity cancer, brain and nervous system cancer, tracheal, bronchus, and lung cancer, gallbladder and biliary tract cancer, malignant skin melanoma, leukemia, Hodgkin lymphoma, multiple myeloma, and other cancers.

Data Fields The dataset includes the following data fields:

• Country: The country where the cancer death occurred.
• Code: The country code for the country where the cancer death occurred.
• Year: The year in which the cancer death occurred.
• Liver cancer: The number of cancer deaths from liver cancer in the country in the year.
• Kidney cancer: The number of cancer deaths from kidney cancer in the country in the year.
• Larynx cancer: The number of cancer deaths from larynx cancer in the country in the year.
• Breast cancer: The number of cancer deaths from breast cancer in the country in the year.
• Thyroid cancer: The number of cancer deaths from thyroid cancer in the country in the year.
• Stomach cancer: The number of cancer deaths from stomach cancer in the country in the year.
• Bladder cancer: The number of cancer deaths from bladder cancer in the country in the year.
• Uterine cancer: The number of cancer deaths from uterine cancer in the country in the year.
• Ovarian cancer: The number of cancer deaths from ovarian cancer in the country in the year.
• Cervical cancer: The number of cancer deaths from cervical cancer in the country in the year.
• Prostate cancer: The number of cancer deaths from prostate cancer in the country in the year.
• Pancreatic cancer: The number of cancer deaths from pancreatic cancer in the country in the year.
• Esophageal cancer: The number of cancer deaths from esophageal cancer in the country in the year.
• Testicular cancer: The number of cancer deaths from testicular cancer in the country in the year.
• Nasopharynx cancer: The number of cancer deaths from nasopharynx cancer in the country in the year.
• Other pharynx cancer: The number of cancer deaths from other pharynx cancer in the country in the year.
• Colon and rectum cancer: The number of cancer deaths from colon and rectum cancer in the country in the year.
• Non-melanoma skin cancer: The number of cancer deaths from non-melanoma skin cancer in the country in the year.
• Lip and oral cavity cancer: The number of cancer deaths from lip and oral cavity cancer in the country in the year.
• Brain and nervous system cancer: The number of cancer deaths from brain and nervous system cancer in the country in the year.
• Tracheal, bronchus, and lung cancer: The number of cancer deaths from tracheal, bronchus, and lung cancer in the country in the year.
• Gallbladder and biliary tract cancer: The number of cancer deaths from gallbladder and biliary tract cancer in the country in the year.
• Malignant skin melanoma: The number of cancer deaths from malignant skin melanoma in the country in the year.
• Leukemia: The number of cancer deaths from leukemia in the country in the year.
• Hodgkin lymphoma: The number of cancer deaths from Hodgkin lymphoma in the country in the year.
• Multiple myeloma: The number of cancer deaths from multiple myeloma in the country in the year.
• Other cancers: The number of cancer deaths from other cancers in the country in the year.

Data Source The data in this dataset was collected from the World Health Organization (WHO). The WHO collects data on cancer deaths from countries around the world.

Usage This dataset can be used to study cancer deaths by country, type, and year. It can also be used to compare cancer death rates between different countries or over time.

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Lung Cancer Mortality Data

Cancer Rates for Lake County Illinois. Explanation of field attributes: Colorectal Cancer - Cancer that develops in the colon (the longest part of the large intestine) and/or the rectum (the last several inches of the large intestine). This is a rate per 100,000. Lung Cancer – Cancer that forms in tissues of the lung, usually in the cells lining air passages. This is a rate per 100,000. Breast Cancer – Cancer that forms in tissues of the breast. This is a rate per 100,000. Prostate Cancer – Cancer that forms in tissues of the prostate. This is a rate per 100,000. Urinary System Cancer – Cancer that forms in the organs of the body that produce and discharge urine. These include the kidneys, ureters, bladder, and urethra. This is a rate per 100,000. All Cancer – All cancers including, but not limited to: colorectal cancer, lung cancer, breast cancer, prostate cancer, and cancer of the urinary system. This is a rate per 100,000.

BackgroundBetter information on lung cancer occurrence in lifelong nonsmokers is needed to understand gender and racial disparities and to examine how factors other than active smoking influence risk in different time periods and geographic regions. Methods and FindingsWe pooled information on lung cancer incidence and/or death rates among self-reported never-smokers from 13 large cohort studies, representing over 630,000 and 1.8 million persons for incidence and mortality, respectively. We also abstracted population-based data for women from 22 cancer registries and ten countries in time periods and geographic regions where few women smoked. Our main findings were: (1) Men had higher death rates from lung cancer than women in all age and racial groups studied; (2) male and female incidence rates were similar when standardized across all ages 40+ y, albeit with some variation by age; (3) African Americans and Asians living in Korea and Japan (but not in the US) had higher death rates from lung cancer than individuals of European descent; (4) no temporal trends were seen when comparing incidence and death rates among US women age 40–69 y during the 1930s to contemporary populations where few women smoke, or in temporal comparisons of never-smokers in two large American Cancer Society cohorts from 1959 to 2004; and (5) lung cancer incidence rates were higher and more variable among women in East Asia than in other geographic areas with low female smoking. ConclusionsThese comprehensive analyses support claims that the death rate from lung cancer among never-smokers is higher in men than in women, and in African Americans and Asians residing in Asia than in individuals of European descent, but contradict assertions that risk is increasing or that women have a higher incidence rate than men. Further research is needed on the high and variable lung cancer rates among women in Pacific Rim countries.

As of 2022, the age-standardized mortality rate of lung cancer worldwide was **** per 100,000 population. At this time, the mortality rate of lung cancer was highest in Polynesia. This statistic shows the age-standardized mortality rate of lung cancer worldwide as of 2022, by region.