An AI model to detect Alzheimer’s disease at an earlier stage

Researchers at Texas A&M are training an AI to analyse multimodal patient data in order to identify the stage of Alzheimer’s disease at an earlier stage.

Researchers at Texas A&M University are developing an artificial intelligence model to facilitate earlier diagnosis of Alzheimer's disease. The team, led by researcher Tianbao Yang, is harnessing AI's ability to spot complex patterns in large datasets to analyze a patient's multimodal information and determine what stage of the disease they are in.

This approach is part of a broader research dynamic on AI-assisted diagnosis of neurodegenerative diseases, where several teams are also exploring blood biomarkers to improve the accuracy of diagnoses made by general practitioners, with the aim of bringing their reliability closer to that of specialists.