Can sleep help in detecting the risk of developing various health conditions? Researchers from Stanford Medicine say yes!
Experts have developed a new artificial intelligence model that can use the physiological recordings from one night’s sleep to predict a person’s risk of developing more than 100 health conditions.
The AI model, known as SleepFM, was trained on nearly 600,000 hours of sleep data collected from 65,000 participants. As per the researchers, the new study is the first to use AI to analyse such large-scale sleep data.
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“From an AI perspective, sleep is relatively understudied. There’s a lot of other AI work that’s looking at pathology or cardiology, but relatively little looking at sleep, despite sleep being such an important part of life,” said James Zou, PhD, associate professor of biomedical data science at Stanford University and co-senior author of the study.
The AI model has analysed more than 1,000 disease categories in the health records and found 130 that could be predicted with reasonable accuracy by a patient’s sleep data.
The predictions were particularly strong for diseases like cancers, pregnancy complications, circulatory conditions and mental disorders.
What are the diseases the AI model excelled in predicting?
As per Stanford Medicine, SleepFM excelled at predicting Parkinson’s disease, dementia, hypertensive heart disease, heart attack, prostate cancer, breast cancer and death.
Meanwhile, OpenAI has launched a ChatGPT Health tab that answers health-related questions. Tasks such as understanding recent test results, preparing for doctor appointments, getting diet advice and workout routines, or evaluating tradeoffs between different insurance options based on individual healthcare patterns can be done through the new tab.
