Nature Podcast This AI tool predicts your risk of 1,000 diseases — by looking at your medical records
Sep 17, 2025
Moritz Gerstung, a computational biologist at the German Cancer Research Centre, discusses the groundbreaking Delphi2M AI tool that predicts an individual's risk of over 1,000 diseases using their health records. The system, trained on extensive data from 400,000 individuals, aims to streamline healthcare by forecasting disease progression. Gerstung also highlights concerns about biases in the AI’s training data and its potential transformative role in population health management. Additionally, the podcast explores intriguing research on AI's influence on unethical behavior in task delegation.
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Sequence-Based Health Forecasting
- Delphi2M predicts risks for over 1,000 diseases by learning patterns from large medical records.
- It models sequences of diagnoses like words in a sentence and factors in timing to forecast future risks.
Probabilities Not Certainties
- Delphi2M combines UK Biobank records with lifestyle data to individualize risk estimates.
- It reports probabilities (e.g., one in 100) rather than deterministic predictions about future illness.
Performance Versus Specialized Models
- Delphi2M matched or slightly outperformed specialist algorithms across many diseases.
- It performed slightly worse on diabetes where molecular markers gave competitors an edge.