Opening the black box: interpretable machine learning for predictor finding of metabolic syndrome

OBJECTIVE: The internal workings ofmachine learning algorithms are complex and considered as low-interpretation "black box" models, making it difficult for domain experts to understand and trust these complex models. The study uses metabolic syndrome (MetS) as the entry point to analyze an...

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Detalles Bibliográficos
Autores principales: Zhang, Yan, Zhang, Xiaoxu, Razbek, Jaina, Li, Deyang, Xia, Wenjun, Bao, Liangliang, Mao, Hongkai, Daken, Mayisha, Cao, Mingqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9419421/
https://www.ncbi.nlm.nih.gov/pubmed/36028865
http://dx.doi.org/10.1186/s12902-022-01121-4

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