Making the most out of timeseries symptom data: A machine learning study on symptom predictions of internet-based CBT

Making the most out of timeseries symptom data: A machine learning study on symptom predictions of internet-based CBT

Objective: Predicting who will not benefit enough from Internet-Based Cognitive Behavioral (ICBT) Therapy early on can assist in better allocation of limited mental health care resources. Repeated measures of symptoms during treatment is the strongest predictor of outcome, and we want to investigate...

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Bibliographic Details
Main Authors: Nils Hentati Isacsson, Kirsten Zantvoort, Erik Forsell, Magnus Boman, Viktor Kaldo
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Internet Interventions
Subjects:
Machine learning
Prediction
Treatment outcome
Adaptive treatment strategy
Precision psychiatry
Timeseries symptom
Online Access:http://www.sciencedirect.com/science/article/pii/S2214782924000666
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