Can Machine Learning Help Anticipate Death from Cancer?

Can a machine-learning algorithm detect the intimations of mortality among a group of cancer patients, telling doctors and patients who should be having conversations about the end? A particular machine-learning computer model can do so, based on the factors found in electronic health records (EHRs), according to a new paper by University of Pennsylvania School of Medicine researchers in the journal JAMA Network Open. "In this cohort study, machine learning algorithms based on structured electronic health record data accurately identified patients with cancer at risk of short-term mortality," they wrote. Of the patients flagged as being "high priority" by the machine, 51% died within a 180-day window, according to the authors. Less than 4% of the patients deemed "lower priority" died in the same time frame, according to the findings.