Could AI help clinicians to predict Alzheimer's disease before it develops?

A new AI model, developed by IBM Research and Pfizer, has used short, non-invasive and standardized speech tests to help predict the eventual onset of Alzheimer's disease within healthy people with an accuracy of 0.7 and an AUC of 0.74 (area under the curve). These predictions were made against data samples from a group of healthy individuals who eventually did or did not develop the disease later in life, allowing researchers to verify the accuracy of the AI model's prediction. This is a significant increase over predictions based on clinical scales (59%), which is a prediction based on other available biomedical data from a patient, as well as random choice (50%). The model uses natural language processing to analyze one- to two-minute speech samples from a brief, clinically administered cognitive test. These short samples of language data were provided by the Framingham Heart Study, a long-running study tracking various aspects of health in more than 5,000 people and their families since 1948.