DiabetesDeepInsight-CSV: Multi-Source Type 2 Diabetes Prediction Data

Over 300,000 records combine Pima Indians, BRFSS surveys, and Retinopathy Debrecen datasets for Type 2 Diabetes prediction. This collection integrates clinical indicators like blood tests and demographics with retinal image-derived features. The dataset was authored by TahaGorji and last updated on Hugging Face in June 2025.

Use Cases

• Predicting Type 2 Diabetes risk based on combined clinical and lifestyle factors mentioned in the description
• Analyzing correlations between retinopathy features and diabetes progression based on retinal image-derived data
• Training multi-source fusion models for medical diagnosis using the integrated dataset collection
• Benchmarking machine learning algorithms on a dataset combining demographic, behavioral, and clinical variables

Strengths

• Integrates over 300,000 records from three distinct sources
• Combines clinical indicators, demographics, lifestyle factors, and retinal image-derived features
• Specifically designed for Type 2 Diabetes prediction, providing a clear application focus

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is an aggregate figure; individual dataset sizes and specific record counts are unknown
• Description metadata is limited; actual data quality and integration methodology require manual inspection

Provenance

Source

Combines Pima Indians Diabetes Dataset, BRFSS surveys, and Retinopathy Debrecen dataset

Collection Method

Multi-dataset fusion, likely compiled from existing public sources

Freshness

Last updated 2025-06-06 19:00:28