Abstract
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 language | English (US) |
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Article number | 14 |
Journal | Translational Vision Science and Technology |
Volume | 9 |
Issue number | 2 |
DOIs | |
State | Published - 2020 |
Keywords
- Artificial intelligence
- Deep learning
- Machine learning
ASJC Scopus subject areas
- Biomedical Engineering
- Ophthalmology