首页|University of Dundee Reports Findings in Machine Learning (Electroconvulsive the rapy response and remission in moderate to severe depressive illness: a decade o f national Scottish data)
University of Dundee Reports Findings in Machine Learning (Electroconvulsive the rapy response and remission in moderate to severe depressive illness: a decade o f national Scottish data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Dundee, United Kingdom , by NewsRx editors, research stated, "Despite strong evidence of efficacy of el ectroconvulsive therapy (ECT) in the treatment of depression, no sensitive and s pecific predictors of ECT response have been identified. Previous meta-analyses have suggested some pre-treatment associations with response at a population lev el." Our news journalists obtained a quote from the research from the University of D undee, "Using 10 years (2009-2018) of routinely collected Scottish data of peopl e with moderate to severe depression ( = 2074) receiving ECT we tested two hypot heses: (a) that there were significant group-level associations between post-ECT clinical outcomes and pre-ECT clinical variables and (b) that it was possible t o develop a method for predicting illness remission for individual patients usin g machine learning. Data were analysed on a group level using descriptive statis tics and association analyses as well as using individual patient prediction wit h machine learning methodologies, including cross-validation. ECT is highly effe ctive for moderate to severe depression, with a response rate of 73% and remission rate of 51%. ECT response is associated with older ag e, psychotic symptoms, necessity for urgent intervention, severe distress, psych omotor retardation, previous good response, lack of medication resistance, and c onsent status. Remission has the same associations except for necessity for urge nt intervention and, in addition, history of recurrent depression and low suicid e risk. It is possible to predict remission with ECT with an accuracy of 61% . Pre-ECT clinical variables are associated with both response and remission and can help predict individual response to ECT."
DundeeUnited KingdomEuropeCyborgsElectroconvulsive TherapyEmerging TechnologiesHealth and MedicineMachine LearningRisk and Prevention
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