Decrypt's Art, Fashion, and Entertainment Hub. Discover SCENE New Research: AI Predicts Alzheimer's Disease Seven Years in Advance According to a recent study featured by the U. S. National Institute of Health, a groundbreaking AI system has the ability to predict Alzheimer's disease up to seven years before the onset of symptoms. This discovery has the potential to revolutionize early treatment options for the disease. By analyzing patients' previous medical records, researchers successfully trained the AI model to accurately predict Alzheimer's disease with a 70% success rate seven years in advance, and an impressive 80% success rate the day before diagnosis. The study further revealed that the model's predictive accuracy improved to 90% when additional demographic details such as birth year, gender, ethnicity, and race were included. The researchers noted that electronic health records have become a valuable resource in understanding and predicting complex diseases like Alzheimer's. They drew insights from prior studies that utilized health records to track the progression of the disease, as well as models that predicted dementia based on clinical data. The burden of neurodegenerative disorders, including Alzheimer's disease, is projected to increase significantly in aging populations.

The researchers emphasized the devastating impact these disorders have on patients and caregivers alike, given the costly and challenging nature of their cognitive symptoms. To conduct the study, experts from the University of California–San Francisco compiled clinical data from over 250, 000 individuals using their extensive medical records database. This data spanned from 1980 to 2021 and included nearly 3, 000 Alzheimer's patients. The AI models were trained on 70% of the patient records, comprising both Alzheimer's patients and controls who had not been diagnosed with the disease. The remaining 30% of records were reserved for the evaluation phase of the study. The AI demonstrated a remarkable ability to predict the onset of Alzheimer's disease with high accuracy. The study also identified several predictors that contribute to Alzheimer's risk, including high cholesterol and fat levels, congestive heart failure, dizziness, cataracts, and deteriorating cartilage between bone joints. Notably, osteoporosis was singled out as a female-specific predictor of Alzheimer's risk, showing a faster progression to the disease among female individuals with osteoporosis compared to female controls. The implications of this level of predictive power are significant in the battle against Alzheimer's, a disease that currently lacks a cure. The ability to identify prospective patients years in advance could potentially lead to innovative strategies for slowing down or halting the disease's progression before irreversible damage occurs. Despite multiple attempts to seek comment, the lead researcher was unavailable for response. (Edited by Ryan Ozawa)