Researchers at the University of California, San Francisco recently developed an AI algorithm that can identify patients at risk for developing Alzheimer’s disease up to seven years in advance, according to aThe researchers reported that their AI models predicted Alzheimer’s disease up to seven years in advance with 72% accuracy. machine learning are enabling disease prediction and accelerating precision medicine in an effort to improve patient outcomes.
The UCSF researchers used a precision medicine database tool called SPOKE that was developed in the lab of UCSF neurology professor Sergio Barazini, Ph.D., inwith Sharat Israni, Ph.D., the executive director of UCSF’s Bakar Computational Health Sciences Institute.
The UCSF team set out to develop AI models based on clinical data from electronic health records that can predict Alzheimer's disease and used the SPOKE network to help understand the possible biological reasons for the identified predictors. From over 5.5 million electronic health records from 1980-2021, the data used for the study include nearly 3,000 patients diagnosed with Alzheimer's by the UCSF Memory and Aging Center.