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Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach
OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient’s expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to generate personalized predictions of symptom traje...
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| Pubblicato in: | Int J Eat Disord |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8273095/ https://ncbi.nlm.nih.gov/pubmed/33811362 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/eat.23510 |
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