Revolutionary AI Model Predicts Future Health Risks Like a Weather Forecast

Sun Oct 19 2025 20:03:58 GMT+0300 (Eastern European Summer Time)

Scientists unveil Delphi-2M, an AI model capable of predicting health problems over a decade in advance, marking a potential breakthrough in proactive medical care.

A new AI model developed by researchers can forecast individuals' health risks for over 1,000 diseases, resembling weather predictions. By analyzing medical records, the Delphi-2M tool aims to identify high-risk patients early, offering a new approach to preventive healthcare. Though still in research phases, the model could transform how medical professionals anticipate and address future health trends.

Artificial intelligence can predict people's health problems over a decade into the future, say scientists.

The technology has learned to spot patterns in people's medical records to calculate their risk of more than 1,000 diseases.

The researchers say it is like a weather forecast that anticipates a 70% chance of rain – but for human health.

Their vision is to use the AI model to spot high-risk patients to prevent disease and help hospitals understand demand in their area, years ahead of time.

The model – called Delphi-2M - uses technology similar to AI chatbots like ChatGPT, trained to analyze medical records and predict future health events.

While it doesn't predict exact incidents, it estimates the likelihood of various diseases, allowing for proactive healthcare measures.

Developed using UK hospital data and validated with records from Denmark, the model shows promising accuracy in predicting diseases such as type 2 diabetes and heart attacks.

The AI tool, while not yet ready for clinical use, aims to identify high-risk patients early and potentially offer tailored lifestyle advice or medication to prevent diseases.

This innovative approach could transform healthcare by accurately predicting future health trends and enhancing resource planning for medical facilities.

However, the model needs further refinement and testing, and researchers emphasize that it is still in the research phase, requiring proper regulation and testing before clinical deployment.