首页|University of Calgary Cumming School of Medicine Researchers Broaden Understandi ng of Machine Learning (Achieving high interrater reliability in establishing d ata labels: a retrospective chart review study)
University of Calgary Cumming School of Medicine Researchers Broaden Understandi ng of Machine Learning (Achieving high interrater reliability in establishing d ata labels: a retrospective chart review study)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on artificial intelligenc e is the subject of a new report. According tonews reporting out of Calgary, Ca nada, by NewsRx editors, research stated, “In medical research, theeffectivenes s of machine learning algorithms depends heavily on the accuracy of labeled data . This study aimed to assess inter-rater reliability (IRR) in a retrospective el ectronic medical chart review to createhigh quality labeled data on comorbiditi es and adverse events (AEs).”
University of Calgary Cumming School of MedicineCalgaryCanadaNorth and Central AmericaCyborgsEmerging Technolo giesMachine Learning
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