Revolutionary AI Method Forecasts Alzheimer’s Decades Before Symptoms

UCSF scientists used a computer model to predict Alzheimer’s onset, spotting key signs in many patients.

By Sunil Sonkar 2 Min Read
2 Min Read
Revolutionary AI Method Forecasts Alzheimer’s Decades Before Symptoms

Scientists at UC San Francisco used a computer model to guess when Alzheimer’s Disease might begin. They looked at details of many patients in the study and found some important signs that hint Alzheimer’s might happen later on.

The research discovered that having high cholesterol is a big factor in guessing if someone might get Alzheimer’s. It is irrespective of gender. Notably, for women, osteoporosis—a condition characterized by weakening of the bones—emerges as a significant predictor. The discovery tells us that having strong bones might lower the chances of getting dementia, hinting there might be hidden connections between them in our bodies.

The study is published in Nature Aging magazine. It explains how AI might change how we find and treat Alzheimer’s and other serious diseases early. Alice Tang, who was in charge of the study, thinks using AI to spot patterns in patient information is crucial. It helps us learn more about how diseases begin in our bodies.


By harnessing UCSF’s SPOKE tool—a sophisticated database integration platform—the researchers identified genetic links associated with Alzheimer’s including a notable connection between osteoporosis and the MS4A6A gene in women.

Dr. Marina Sirota, who led the study, says using AI is important to understand how diseases work and land people at risk. Many experts teamed up for the study and this reveals how working together helps us understand medicine better and take better care of patients.

The new AI method can guess when Alzheimer’s might start with 72% accuracy, giving hope for early help and treatments made just for each person.

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