Clinical Psychopharmacology and Neuroscience indexed in CAS, DOI/Crossref, EMBASE, Korea Citation Index (KCI), KoreaMed, Korea Medical Citation Index (KoMCI), PubMed, PubMed Central (PMC), SCOPUS, SCI-expanded (SCIE), and Google Scholar:eISSN 2093-4327   pISSN 1738-1088

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Fig. 1. An example of the machine learning framework for forecasting antidepressant treatment response. The machine learning model comprises two major components including a feature selection algorithm and a predictive algorithm. The feature selection algorithm produces a small subset of good features, which serves as the training dataset for subsequent analysis. The training dataset serves as the input for the predictive algorithm. The predictive algorithm estimates the prediction of antide-pressant treatment outcome from the training dataset. SNPs, single nucleotide polymorphisms.
Clin Psychopharmacol Neurosci 2021;19:577~588
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