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Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study

BACKGROUND: Artificial intelligence and digital health care have substantially advanced to improve and enhance medical diagnosis and treatment during the prolonged period of the COVID-19 global pandemic. In this study, we discuss the development of prediction models for the self-diagnosis of polycys...

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Detalles Bibliográficos
Autores principales:	Zigarelli, Angela, Jia, Ziyang, Lee, Hyunsun
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2022
Materias:	Early Reports
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8965679/ https://www.ncbi.nlm.nih.gov/pubmed/35289757 http://dx.doi.org/10.2196/29967

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