This file is related to Piezo1-mechanically sensitive channel study

Context

This data comes from aggregation of the tables available on the NIH's National Cancer Institutes State Cancer Profiles, specifically with their incidence tables.

The objective of the State Cancer Profiles Web site is to provide a system to characterize the cancer burden in a standardized manner in order to motivate action, integrate surveillance into cancer control planning, characterize areas and demographic groups, and expose health disparities. The focus is on cancer sites for which there are evidence based control interventions. Interactive graphics and maps provide visual support for deciding where to focus cancer control efforts.

Content

This data has cancer Incidence rates broken down by US County and includes data aggregated from 2012-2016. It has both incidence rates per 100k as well as yearly totals averaged over that period

Potential Future Work

This data is summarized across other potentially illuminating fields. The State Cancer Profiles can be further broken down by cancer area, race/ethnicity, sex, age, and stage. If more fidelity on the data would be helpful please add it to the discussion section and I can work on adding it!

Data Use Restrictions

Read Carefully Before Using

By using these data, you signify your agreement to comply with the following statutorily based requirements.

The Public Health Service Act (42 U.S.C. 242m(d)) provides that the data collected by the National Center for Health Statistics (NCHS) may be used only for the purpose for which they were obtained; any effort to determine the identity of any reported cases, or to use the information for any purpose other than for statistical reporting and analysis, is against the law. The National Program of Cancer Registries (NPCR), Centers for Disease Control and Prevention (CDC), has obtained an assurance of confidentiality pursuant to Section 308(d) of the Public Health Service Act, 42 U.S.C. 242m(d). This assurance provides that identifiable or potentially identifiable data collected by the NPCR may be used only for the purpose for which they were obtained unless the person or establishment from which they were obtained has consented to such use. Any effort to determine the identity of any reported cases, or to use the information for any purpose other than statistical reporting and analysis, is a violation of the assurance.

Therefore users will: - Use the data for statistical reporting and analysis only. - Make no attempt to learn the identity of any person or establishment included in these data. - Make no disclosure or other use of the identity of any person or establishment discovered inadvertently, and advise the appropriate contact for the data provider. In addition to immediately notifying "Contact Us" of the potential disclosure, - For mortality data, notify the Confidentiality Officer at the National Center for Health Statistics (Alvan O. Zarate, Ph.D.), 3311 Toledo Road, Rm 7116, Hyattsville, MD 20782, Phone: 301-458-4601, Fax: 301-458-4021) - For incidence data notify both the Federal agency that provided the data and notify the relevant state or metropolitan area cancer registryExternal Web Site Policy, of any such discovery. - For CDC's National Program of Cancer Registries (NPCR) areas, notify the Associate Director for Science, Office of Science Policy and Technology Transfer, CDC, Mailstop D-50, 1600 Clifton Road, N.E., Atlanta, Georgia, 30333, Phone: 404-639-7240) - For NCI's Surveillance, Epidemiology, and End Results (SEER) Program registry areas, notify the Branch Chief of the Cancer Statistics Branch of the Surveillance Research Program, Division of Cancer Control and Population Sciences, NCI, BG 9609 MSC 9760, 9609 Medical Center Drive, Bethesda, MD 20892-9760, Phone: 301-496-8510, Fax: 301-496-9949.

PurposeThe Mid Sweden Cohort (MSC) was established to investigate self-perceived oral and general health among two groups of aging individuals in two counties (Örebro and Östergötland) in Sweden. For internal and external data validation, we linked collected data on health status, behavior, sociodemographic circumstances, and dependency with national register data from Statistics Sweden and compared non-respondents and those lost to follow-up to respondents.ParticipantsMSC is based on a longitudinal multiwave study of aging men and women who answered a cross-sectional questionnaire from MSC: (1) the 1992 cohort including participants aged 50 years in 1992 and (2) the 2007 cohort including participants aged 75 years in 2007. After the baseline surveys, data collection was conducted every 5 years, with the latest wave from 2017 included in our validation. Between 1992 and 2017, 8,879 participants were included in cohort 1, while 5,191 individuals were included in cohort 2 between 2007 and 2017.ResultsAfter linking self-reported data with national register-based data and analyzing loss to follow-up and non-response numbers, we found that, besides age, factors such as being male, having immigrant status, lower income and education level, being single, and being in poor health were predictors of non-response and loss to follow-up, aligning with the findings of other studies. Based on our results, we conclude the MSC is reliable for further research, provided the observed bias is taken into account.Future plansUsing the MSC, we aim to analyze self-reported oral health changes as a predictor of dependency in the elderly and track oral health status over time. Furthermore, we plan to link data with register-based clinical oral health records. We also intend to add the 2022 wave data and future waves into the existing dataset.

This report contains the results of the 2024 Licensed Master’s Social Worker (LMSW) Workforce Survey. Among all LMSWs, 987 voluntarily participated in this survey. The Virginia Department of Health Professions’ Healthcare Workforce Data Center (HWDC) administers the survey during the license renewal process, which takes place every June for LMSWs. These survey respondents represent 64% of the 1,531 LMSWs licensed in the state and 98% of renewing practitioners.

RTLS in Healthcare Market is predicted to reach USD 8.02 billion by 2030 with a CAGR of 18.1%

Overview

The Mesenchymal Stem Cells (MSC) market is projected to grow significantly over the next decade. Market size is anticipated to expand from USD 3 billion in 2023 to approximately USD 10 billion by 2033. This trajectory represents a compound annual growth rate (CAGR) of 12.6% during 2024–2033. Growth is driven by rising clinical demand, ageing populations, and clearer regulatory pathways. Together, these forces create a strong foundation for the adoption of MSC-based therapies across multiple disease areas.

Demand remains high due to the global burden of musculoskeletal and degenerative conditions. According to the World Health Organization (WHO), musculoskeletal disorders affect about 1.71 billion people worldwide and remain the leading cause of disability. Osteoarthritis alone impacted around 528 million people in 2019. These figures highlight the scale of the patient population in need of effective treatment. MSC therapies are being developed to address unmet needs in joint, spine, cardiovascular, and immune conditions, ensuring a consistent demand pull.

Demographic shifts further reinforce market growth. The United Nations projects a sharp increase in the global 65+ population in the coming decades. Older adults face higher risks of degenerative and inflammatory diseases, directly correlating with MSC-targeted applications. This trend supports continued research investment and clinical development. As the ageing population rises, healthcare systems and industry stakeholders are prioritizing regenerative solutions that preserve mobility, manage pain, and delay the need for invasive surgery.

Clinical research is also accelerating market expansion. ClinicalTrials.gov currently lists over 1,700 MSC-related studies worldwide. These cover diverse indications such as orthopedics, neurology, cardiology, pulmonology, and immune disorders. The scale of these investigations ensures continuous data generation on safety, efficacy, and process optimization. Results from such trials, alongside new partnerships and translational research, enhance confidence in MSC programs. This steady pipeline sustains near-term momentum while laying the foundation for long-term adoption.

Regulatory Support and Market Enablers

Regulatory progress provides significant support to the MSC sector. In the United States, the Food and Drug Administration (FDA) offers the Regenerative Medicine Advanced Therapy (RMAT) designation. This framework accelerates clinical development for qualifying products and enables greater interaction with regulators. Data from the FDA highlight an increase in RMAT requests and approvals, showing sustained developer interest. In Europe, the European Medicines Agency (EMA) regulates cell-based products under the Advanced Therapy Medicinal Products (ATMP) classification, further streamlining market pathways.

Manufacturing guidelines also strengthen market readiness. The World Health Organization’s good manufacturing practice (GMP) standards for biological products are widely referenced by regulators and manufacturers. Adherence to GMP ensures consistent sourcing, testing, and quality control of living-cell therapies. Similarly, FDA guidance clarifies expectations for comparability in cellular therapy manufacturing. Together, these frameworks reduce technical risks, support scale-up, and give investors confidence in the transition from clinical to commercial production.

The persistent burden of musculoskeletal and degenerative disease ensures long-term commercial viability for MSC therapies. WHO data and UN population projections confirm that rising prevalence will continue to pressure healthcare systems. MSC approaches are positioned as viable solutions to preserve function, reduce chronic pain, and postpone costly surgical interventions. This makes them strategically attractive to healthcare providers and payers seeking durable outcomes.

Looking ahead, the sector’s outlook remains cautiously optimistic. Market growth will be driven by ageing demographics, a robust clinical pipeline, supportive regulations, and harmonized manufacturing practices. Success, however, depends on evidence generation in well-controlled trials and real-world studies. Demonstrating safety, efficacy, and cost-effectiveness will be critical. If developers align with international regulatory standards and deliver measurable patient benefits, the MSC market is expected to achieve sustainable expansion through 2033.

Msc Medical Industry D Tic Limited Ti Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

🇬🇧 English:

This synthetic dataset helps build machine learning models to predict whether a patient is at risk of heart disease. It includes patient attributes such as age, cholesterol, blood pressure, sex, and diabetes history.

Use this dataset to:

• Train classification models (e.g., XGBoost, Decision Tree)
• Analyze the relationship between health metrics and heart disease
• Practice healthcare-related ML without privacy concerns

Features:

• age: Age of the patient
• cholesterol: Cholesterol level (mg/dL)
• bp: Blood pressure (mmHg)
• sex: Biological sex (Male/Female)
• diabetes: Diabetes status (Yes/No)
• heart_disease: Presence of heart disease (1 = Yes, 0 = No)

🇹🇷 Türkçe:

Bu sentetik veri seti, hastaların kalp hastalığı riski taşıyıp taşımadığını tahmin etmeye yönelik makine öğrenmesi modelleri geliştirmek için tasarlanmıştır. Yaş, kolesterol, tansiyon, cinsiyet ve diyabet bilgileri gibi özellikleri içerir.

Bu veri seti ile:

• XGBoost ve Decision Tree gibi sınıflandırma modelleri eğitilebilir
• Sağlık verileriyle risk analizi yapılabilir
• Gizlilik endişesi olmadan sağlık odaklı projeler geliştirilebilir

This data includes the name and location of active food service establishments and the violations that were found at the time of the inspection. Active food service establishments include only establishments that are currently operating. This dataset excludes inspections conducted in New York City (https://data.cityofnewyork.us/Health/Restaurant-Inspection-Results/4vkw-7nck), Suffolk County (http://apps.suffolkcountyny.gov/health/Restaurant/intro.html) and Erie County (http://www.healthspace.com/erieny). Inspections are a “snapshot” in time and are not always reflective of the day-to-day operations and overall condition of an establishment. Occasionally, remediation may not appear until the following month due to the timing of the updates. Update frequencies and availability of historical inspection data may vary from county to county. Some counties provide this information on their own websites and information found there may be updated more frequently. This dataset is refreshed on a monthly basis. The inspection data contained in this dataset was not collected in a manner intended for use as a restaurant grading system, and should not be construed or interpreted as such. Any use of this data to develop a restaurant grading system is not supported or endorsed by the New York State Department of Health. Historical inspection data through 2005 is also available. Inactive (closed) establishments can be found at: https://health.data.ny.gov/Health/Food-Service-Establishment-Inspections-Beginning-2/aaxz-j6pj. For more information, visit http://www.health.ny.gov/regulations/nycrr/title_10/part_14/subpart_14-1.htm or go to the “About” tab.

Patients often provide untruthful information about their health to avoid embarrassment, evade treatment, or prevent financial loss. Privacy disclosures (e.g. HIPAA) intended to dissuade privacy concerns may actually increase patient lying. We used new mouse tracking-based technology to detect lies through mouse movement (distance and time to response) and patient answer adjustment in an online controlled study of 611 potential patients, randomly assigned to one of six treatments. Treatments differed in the notices patients received before health information was requested, including notices about privacy, benefits of truthful disclosure, and risks of inaccurate disclosure. Increased time or distance of device mouse movement and greater adjustment of answers indicate less truthfulness. Mouse tracking revealed a significant overall effect (p < 0.001) by treatment on the time to reach their final choice. The control took the least time indicating greater truthfulness and the privacy + risk group took the longest indicating the least truthfulness. Privacy, risk, and benefit disclosure statements led to greater lying. These differences were moderated by gender. Mouse tracking results largely confirmed the answer adjustment lie detection method with an overall treatment effect (p < .0001) and gender differences (p < .0001) on truthfulness. Privacy notices led to decreased patient honesty. Privacy notices should perhaps be administered well before personal health disclosure is requested to minimize patient untruthfulness. Mouse tracking and answer adjustment appear to be healthcare lie-detection methods to enhance optimal diagnosis and treatment.

This table is the raw data of all policies, strategies, and action plans included in the study titled "Rehabilitation in national health planning: a narrative review of laws and policies in five European countries" submitted for the Masters of Arts in Health Sciences at the University of Lucerne, Switzerland.

The Umbilical Cord Mesenchymal Stem Cell (UC-MSC) storage market is an emerging segment within the broader field of regenerative medicine, drawing significant interest from both healthcare professionals and expectant parents. This market revolves around the collection and cryogenic storage of mesenchymal stem cells

This file contains the unstructured notes made during archival research on my MSc-thesis project 'Individualised Public Health: a conceptual history of heredity during the interwar years'.

The ability to rise from sitting to standing is critical to an individual’s quality of life, as it is a prerequisite for functional independence. The purpose of the current study was to examine whether test durations as assessed with the instrumented repeated Sit-To-Stand (STS) show stronger associations with health status, functional status and daily physical activity of older adults than manually recorded test durations.

In 63 older participants (mean age 83 ±6.9 years, 51 female), health status was assessed using the European Quality of Life questionnaire and functional status was assessed using the physical function index of the of the RAND-36. Physical performance was measured using a wearable sensor-based STS test. From this test, durations, sub-durations and kinematics of the STS movements were estimated and analysed. In addition, physical activity was measured for one week using an activity monitor and episodes of lying, sitting, standing and locomotion were identified. Associations between STS parameters with health status, functional status and daily physical activity were assessed.

The manually recorded STS times were not significantly associated with health status (p=0.457) and functional status (p=0.055), whereas the instrumented STS times were (both p=0.009). The manually recorded STS durations showed a significant association to daily physical activity for mean sitting durations (p=0.042), but not for mean standing durations (p=0.230) and mean number of locomotion periods (p=0.218). Furthermore, durations of the dynamic Sit to Stand phase of the instrumented STS showed more significant associations with health status, functional status and daily physical activity (all p=0.001) than the static phases standing and sitting (p=0.043-0.422).

In older adults, instrumented STS durations were more strongly associated with participant health status, functional status and physical activity than manually recorded STS durations. Furthermore, instrumented STS allowed assessment of the dynamic phases of the test, which were likely more informative than the static sitting and standing phases.

The attached data-set is a comprehensive and expanded study on women's health and ageing in the city of Shiraz in mid-2019. The statistical population includes all elderly women over 60 years of age living in Shiraz, southern Iran. The sample includes 9117 elderly female and data was collected over the years 2017 till now.

The dataset is a result of the master thesis 'An Interactive Suicide Ideation Self-Test Service for Helping People Resolve Barriers towards Contacting a Suicide Prevention Helpline'. It also includes an R script with details of the analysis. An experimental research was conducted for the topic with measures of participants' motivation levels towards seeking professional psychological help, feeling of being heard, satisfaction with the service and perceived usefulness. The data was collected from participants recruited from Prolific.The type of data is discrete quantitative data.

Medical care for admitted patients is increasingly reallocated to physician assistants (PAs), because of an increased appreciation of continuity of care, pressure to deliver healthcare efficiently, and local shortages of medical doctors (MDs). A PA is a non-physician healthcare professional licensed to practice medicine in defined domains, with variable degrees of professional autonomy. PAs who are employed for medical care for admitted patients usually work in a team compromising both PAs and MDs (i.e. residents, staff physicians or hospitalists). Although there is a worldwide trend of an increase of PAs in the management of hospitalized patients, evidence about the consequences of reallocating inpatient care from MDs to PAs for healthcare outcomes is limited. This study aimed to determine the effects of substitution of inpatient care from MDs to PAs on patients’ lenght of stay, quality and safety of care, patient experiences and costs. Also the impact on guideline adherence on medication prescribing has been investigated. In a multicenter matched-controlled study, the traditional model in which only MDs are employed for inpatient care was compared with a mixed model in which besides MDs also PAs are employed. Thirty-four wards were recruited across the Netherlands. Patients were followed from admission till one month after discharge. In total, 2,307 patients were included

Data scrapped from vlr.gg

Features: -Player: Player Nickname -Country -Team -FirstAgent: Main agent played -SecondAgent: Second agent most played (if not OTP) -MoreThan2Agents: 1 when the player played more than two agents -OTP: 1 when the player only played one agent -Rounds -AverageCombatScore -KillsDeaths: KD -AverageDamagePerRound -KillsPerRound -AssistsPerRound -FirstKillsPerRound -FirstDeathsPerRound -HeadshotPercentage: Headshots*100/all shots -ClutchesPercentage: clutches won/all clutches -MaxKillsPerMap -Kills: Total kills -Deaths: Total deaths -Assists: Total assists -FirstKills -FirstDeaths

This is the data set for the study on the characteristics and motivational factors of applicants of Masters of Health Professions Education program.

With the enactment of the Higher Education Opportunity Act (HEOA) of 2008, five Predominantly Black Institutions are eligible to receive funding to improve graduate education opportunities at the master’s level in mathematics, engineering, physical or natural sciences, computer science, information technology, nursing, allied health or other scientific disciplines where African American students are underrepresented. Types of Projects Institutions may use federal funds for activities that include: Purchase, rental or lease of scientific or laboratory equipment for educational purposes, including instructional and research purposes; Construction, maintenance, renovation and improvement in classroom, library, laboratory and other instructional facilities, including purchase or rental of telecommunications technology equipment or services; Purchase of library books, periodicals, technical and other scientific journals, microfilm, microfiche, and other educational materials, including telecommunications program materials; Scholarships, fellowships, and other financial assistance for needy graduate students to permit the enrollment of students in, and completion of a master’s degree in mathematics, engineering, physical or natural sciences, computer science, information technology, nursing, allied health, or other scientific disciplines in which African Americans are underrepresented; Establishing or improving a development office to strengthen and increase contributions from alumni and the private sector; Assisting in the establishment or maintenance of an institutional endowment to facilitate financial independence pursuant to Section 331; Funds and administrative management, and the acquisition of equipment, including software, for use in strengthening funds management and management information systems; Acquisition of real property that is adjacent to the campus in connection with the construction, renovation, or improvement of, or an addition to, campus facilities; Education or financial information designed to improve the financial literacy and economic literacy of students or the students’ families, especially with regards to student indebtedness and student assistance programs under title IV; Tutoring, counseling, and student service programs designed to improve academic success; Faculty professional development, faculty exchanges, and faculty participation in professional conferences and meetings; and Other activities proposed in the application that are approved by the Secretary as part of the review and acceptance of such application.