首页|Leuphana University Reports Findings in Machine Learning (Making the most out of timeseries symptom data: A machine learning study on symptom predictions of int ernet-based CBT)
Leuphana University Reports Findings in Machine Learning (Making the most out of timeseries symptom data: A machine learning study on symptom predictions of int ernet-based CBT)
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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 originating from Lueneburg, G ermany, by NewsRx correspondents, research stated, "Predicting who will not bene fit enough from Internet-Based Cognitive Behavioral (ICBT) Therapy early on can assist in better allocation of limited mental health care resources. Repeated me asures of symptoms during treatment is the strongest predictor of outcome, and w e want to investigate if methods that explicitly account for time-dependency are superior to methods that do not, with data from (a) only two pre-treatment time points and (b) the pre-treatment timepoints and three timepoints during initial treatment."
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