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Ability of clinical data to predict readmission in Child and Adolescent Mental Health Services

This study addresses the challenge of predicting readmissions in Child and Adolescent Mental Health Services (CAMHS) by analyzing the predictability of readmissions over short, medium, and long term periods. Using health records spanning 35 years, which included 22,643 patients and 30,938 episodes o...

Täydet tiedot

Tallennettuna:
Päätekijät: Kaban Koochakpour, Dipendra Pant, Odd Sverre Westbye, Thomas Brox Røst, Bennett Leventhal, Roman Koposov, Carolyn Clausen, Norbert Skokauskas, Øystein Nytrø
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: PeerJ Inc. 2024-10-01
Sarja:PeerJ Computer Science
Aiheet:
Machine learning
Prediction
Classification
CAMHS
Clustering
Mental health
Linkit:https://peerj.com/articles/cs-2367.pdf
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