Mark Panaggio News Today

AI identifies pain levels from patient data A research team led by Northwestern University faculty and alumni has found it’s possible to understand a patient’s pain level by examining data from vital signs. In a new study, the team developed and applied artificial intelligence (AI), or machine-learning, algorithms to physiological data — including respiratory rate, blood pressure, heart rate, body temperature and oxygen levels — from patients with chronic pain from sickle cell disease. ...

A new study demonstrates that machine-learning strategies can be applied to routinely collected physiological data, such as heart rate and blood pressure, to provide clues about pain levels in people with sickle cell disease. Mark Panaggio of Johns Hopkins University Applied Physics Laboratory and colleagues present these findings in the open-access journal PLOS Computational Biology.