Introduction to machine learning, neural networks, and deep learning

Rene Y. Choi, Aaron S. Coyner, Jayashree Kalpathy-Cramer, Michael Chiang, J. Peter Campbell

Research output: Contribution to journalArticlepeer-review

301 Scopus citations


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.

Original languageEnglish (US)
Article number14
JournalTranslational Vision Science and Technology
Issue number2
StatePublished - 2020


  • Artificial intelligence
  • Deep learning
  • Machine learning

ASJC Scopus subject areas

  • Biomedical Engineering
  • Ophthalmology


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