AI could change managing of Alzheimer's disease - MedicalView

For the study, the researchers used an existing dataset (18,395) from HAPPYneuron. They examined answers to general health screening questions (addressing memory, sleep quality, medications, and medical conditions affecting thinking), demographic information, and test results from a sample of adults who took the MemTrax (M-CRT) test for episodic-memory screening. MemTrax performance and participant features were used as independent attributes: true positive/negative, percent responses/correct, response time, age, sex, and recent alcohol consumption. For predictive modeling, they used demographic information and test scores to predict binary classification of the health-related questions (yes/no) and general health status (healthy/unhealthy), based on the screening questions. "Findings from our study provide an important step in advancing the approach for clinically managing a very complex condition like Alzheimer's disease," said Michael F. Bergeron, Ph.D., senior author and senior vice president of development and applications, SIVOTEC Analytics.