Data · dataset · 2025
Diabetes Risk Prediction Dataset: Demographics, Lifestyle, and Clinical Indicators
Listed in Teesside University Research Data Repository
📄 Dataset Description This dataset contains demographic, lifestyle, and clinical health indicators collected for the purpose of predicting diabetes risk using machine learning techniques.
Description
The data integrates both behavioral and physiological variables to provide a comprehensive view of factors influencing diabetes onset. 📄Content 1. Demographics: Gender, Age 2.
Lifestyle Factors: Physical Activity, Smoking Status, Alcohol Intake, Family History, Hypertension 3. Clinical Measurements: Glucose, Blood Pressure, Skin Thickness, Insulin, BMI, Cholesterol, Diabetes Pedigree Function 4. Target Variable: Outcome (Diabetic / Non-diabetic) 📄Objective The primary goal of this dataset is to support the development and evaluation of classification models that can predict whether an individual is diabetic or non-diabetic based on measurable risk factors. 📄Potential Use Cases 1.
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Building and testing machine learning models for diabetes prediction. 2. Exploring correlations between lifestyle choices and diabetes prevalence. 3. Conducting data analysis in healthcare research and medical decision support systems. 4.
Developing early risk assessment tools for clinical practice. 📄Format File type: CSV Rows: Each row represents an individual record. Columns: Attributes include demographic, lifestyle, clinical features, and diabetes outcome. 📄
Notes
All values are anonymized. The dataset is intended for educational, research, and analytical purposes only. Users should validate models against external datasets before applying in clinical settings.
Links
Where it is published
- DOI doi.org/10.17632/xv25yjbzkm.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Machine learning · Medicine & Health · Public health · Social Science
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/xv25yjbzkm.2 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4206 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Public Health'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |