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Introduction to Machine Learning, Neural Networks, and Deep Learning

PURPOSE: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. METHODS: A systematic literature search in PubMed was performed for articles pertinent to the topic of artificial...

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Detalles Bibliográficos
Autores principales: Choi, Rene Y., Coyner, Aaron S., Kalpathy-Cramer, Jayashree, Chiang, Michael F., Campbell, J. Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347027/
https://www.ncbi.nlm.nih.gov/pubmed/32704420
http://dx.doi.org/10.1167/tvst.9.2.14
Descripción
Sumario:PURPOSE: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. METHODS: A systematic literature search in PubMed was performed for articles pertinent to the topic of artificial intelligence methods used in medicine with an emphasis on ophthalmology. RESULTS: A review of machine learning and deep learning methodology for the audience without an extensive technical computer programming background. CONCLUSIONS: Artificial intelligence has a promising future in medicine; however, many challenges remain. TRANSLATIONAL RELEVANCE: The aim of this review article is to provide the nontechnical readers a layman's explanation of the machine learning methods being used in medicine today. The goal is to provide the reader a better understanding of the potential and challenges of artificial intelligence within the field of medicine.