Boris Babic|Sara Gerke|Theodoros Evgeniou|I. Glenn Cohen
Direct-to-consumer medical machine learning and artificial intelligence applications
INSEAD|INSEAD|Harvard University Press
directtoconsumer medical artificial intelligencemachine learning applications increasingly used variety diagnostic assessments emphasis telemedicine home healthcare covid19 pandemic may stimulate adoption perspective argue artificial intelligencemachine learning regulatory landscape operate differently system designed cliniciansdoctors opposed designed personal use directtoconsumer applications raise unique concerns due nature consumer users tend limited statistical medical literacy risk averse health outcomes creates environment false alarms proliferate burden public healthcare systems medical insurers similar situations exist elsewhere medicine ease frequency artificial intelligencemachine learning apps used increasing prevalence consumer market calls careful reflection effectively regulate suggest regulators strive better understand consumers interact directtoconsumer medical artificial intelligencemachine learning apps particularly diagnostic ones requires focus systems technical specifications argue best regulatory review would also consider technologies social costs widespread use medical artificial intelligence machine learning technologies marketed directly consumers rise authors argue regulatory landscape technologies operate differently system designed personal use designed clinicians doctors