Digital detection of dementia: Using AI to identify undiagnosed dementia

Rising to meet the formidable challenge of the timely diagnosis of dementia, research scientists from Regenstrief Institute, IUPUI and the medical schools of Indiana University and University of Miami are conducting the Digital Detection of Dementia study, a real-world evaluation of the use of an artificial intelligence (AI) tool they developed for early identification of Alzheimer's disease and related dementias in primary care, the setting where most adults receive healthcare. Individuals identified as cognitively impaired will be referred for diagnostic services. The AI tool, called a passive digital marker, is a machine learning algorithm the researchers developed, trained and tested. The tool uses natural language processing to cull unstructured information in combination with structured data from a patient's electronic health record. These could include mention of memory issues, a notation of vascular concerns, comorbid conditions or other factors potentially linked to dementia. "Between 50 to 80 percent of dementia cases are unrecognized by the healthcare system in the U.S. And, if you include patients living with mild cognitive impairment, that number might actually climb to higher than 80 percent of cases that are not recognized," said Regenstrief Institute and Indiana University School of Medicine faculty member Malaz Boustani, M.D., MPH, senior author of the Digital Detection of Dementia study protocol paper, published in the peer reviewed journal Trials.