The Pros and Cons of Using Machine Learning and Interpretable Machine Learning Methods in psychiatry detection applications, specifically depression disorder: A Brief Review. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Hossein_Simchi>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Samira_Tajik>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.48550%2FarXiv.2311.06633>
foaf:homepage	<https://doi.org/10.48550/arXiv.2311.06633>
dc:identifier	DBLP journals/corr/abs-2311-06633 (xsd:string)
dc:identifier	DOI doi.org%2F10.48550%2FarXiv.2311.06633 (xsd:string)
dcterms:issued	2023 (xsd:gYear)
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rdfs:label	The Pros and Cons of Using Machine Learning and Interpretable Machine Learning Methods in psychiatry detection applications, specifically depression disorder: A Brief Review. (xsd:string)
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rdfs:seeAlso	<https://doi.org/10.48550/arXiv.2311.06633>
dc:title	The Pros and Cons of Using Machine Learning and Interpretable Machine Learning Methods in psychiatry detection applications, specifically depression disorder: A Brief Review. (xsd:string)
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