Tielman Van Vleck

Key Points Question Can acoustic features extracted from audio recordings of patient-physician conversations during routine primary care visits be used to screen for cognitive impairment? Findings In this diagnostic study including 966 older adults without diagnosis of cognitive problems, machine learning models trained on acoustic features from recordings of primary care visits achieved a high degree of accuracy and generalizability for predicting cognitive impairment.

Sample collections The NIDDK IBD Genetics Consortium (IBDGC) recruited samples through the following research centers: Cedars Sinai Medical Center, Icahn School of Medicine at Mount Sinai, Montréal-Boston Collaborative IBD Genetic Research Center, Johns Hopkins Genetic Research Center, University of Pittsburgh, University of Toronto and University College London, and a subset of Jewish controls from Cedars-Sinai Medical Center were obtained from The National Laboratory for the Genetics of...