3 recent studies exploring medical AI tools' efficacy

Medical researchers over the past decade have become increasingly interested in the potential of artificial intelligence to transform healthcare for the better by reducing workflow inefficiencies, predicting health outcomes and speeding up diagnoses.

Below are three AI studies that have been published recently:

  1. "Machine learning-based prediction of COVID-19 diagnosis based on symptoms": Researchers used data reported by the Israeli Ministry of Health to develop an AI-powered model that diagnoses COVID-19 by asking eight basic questions.

  2. "Effect of machine learning on dispatcher recognition of out-of-hospital cardiac arrest during calls to emergency medical services": The research team developed a machine learning model that listens to calls to emergency medical services and alerts medical dispatchers of cases of suspected cardiac arrest.

  3. "Identification of suicide attempt risk factors in a national US survey using machine learning": The research team used a survey of American adults to develop a AI-powered suicide attempt risk assesment model, finding the most important factors to be previous suicidal ideation, despondent feelings, recklessness, decreases in accomplishments, younger age, recent financial troubles and lower educational achievement.  

More articles on health IT:
CIOs see business case for more tech investment in 2021
How hospitals use algorithms to prioritize COVID-19 vaccine distribution
Children’s National Hospital, NIH launch COVID-19 diagnostics AI challenge


© Copyright ASC COMMUNICATIONS 2021. Interested in LINKING to or REPRINTING this content? View our policies by clicking here.


Featured Whitepapers

Featured Webinars