Core Insights - An AI model named SleepFM has been developed by researchers at Stanford University to predict the risk of approximately 130 diseases based on a single night's sleep data, including heart disease, dementia, and certain cancers [1][2] - The model was trained using data from 65,000 participants, totaling nearly 600,000 hours of polysomnography data, marking the first use of AI to analyze such a large dataset of sleep information [1] Group 1 - The SleepFM model utilizes polysomnography, which records various physiological signals related to sleep, making it the "gold standard" for sleep assessment [1] - The training data includes records from 35,000 individuals at the Stanford Sleep Center, who have had their sleep and health monitored over 25 years [2] - The model has shown exceptional predictive capabilities for diseases such as Parkinson's, dementia, developmental delays, and cardiovascular diseases, with high accuracy in predicting prostate, breast, and skin cancers [2] Group 2 - Previous research on sleep and disease often focused on single indicators and specific diseases, neglecting the complexity of sleep physiology [2] - The new findings indicate that AI models can understand the "language" of sleep data, enabling flexible and efficient disease prediction [2]

Core Insights - A new AI model named Delphi-2M has been developed to predict health changes throughout a person's life, aiding doctors and health planners in understanding personalized health needs [1] - The model was trained on health data from 400,000 individuals in the UK and tested on nearly 2 million individuals in Denmark, demonstrating the ability to predict the incidence of over 1,000 diseases with accuracy comparable to or better than existing tools [1] - Delphi-2M can simulate potential health change pathways for up to 20 years and generate synthetic data for training other AI models while ensuring privacy protection [1] Industry Implications - The method is expected to help identify individuals at high risk of diseases, guide screening programs, and support long-term healthcare planning [2] - Future versions of the model may incorporate more types of health information, enhancing personalized treatment approaches [2] - Scientists caution that the model may reflect biases present in the training data, and its predictions should not be used for direct medical decision-making until further testing is conducted [2]

Core Insights - Tencent Technology (Shenzhen) Co., Ltd. has obtained a patent for a "disease prediction method, device, equipment, and storage medium," with the authorization announcement number CN115116618B, and the application date was May 2022 [1] Company Overview - Tencent Technology (Shenzhen) Co., Ltd. was established in 2000 and is located in Shenzhen, primarily engaged in software and information technology services [1] - The company has a registered capital of 2 million USD [1] - Tencent Technology has invested in 15 companies and participated in 264 bidding projects [1] - The company holds 5,000 trademark records and 5,000 patent records, along with 533 administrative licenses [1]