Current status and future trends of clinical diagnoses via image-based deep learning

Jie Xu; Kanmin Xue; Kang Zhang

doi:10.7150/thno.38065

Current status and future trends of clinical diagnoses via image-based deep learning

Theranostics. 2019 Oct 12;9(25):7556-7565. doi: 10.7150/thno.38065. eCollection 2019.

Authors

Jie Xu¹, Kanmin Xue², Kang Zhang³

Affiliations

¹ Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Lab, Beijing, China.
² Royal Victorian Eye and Ear Hospital, Melbourne, Victoria 3002, Australia.
³ Faculty of Medicine, Macau University of Science and Technology, Taipa, Macau.

Abstract

With the recent developments in deep learning technologies, artificial intelligence (AI) has gradually been transformed from cutting-edge technology into practical applications. AI plays an important role in disease diagnosis and treatment, health management, drug research and development, and precision medicine. Interdisciplinary collaborations will be crucial to develop new AI algorithms for medical applications. In this paper, we review the basic workflow for building an AI model, identify publicly available databases of ocular fundus images, and summarize over 60 papers contributing to the field of AI development.

Keywords: artificial intelligence; deep learning; machine learning; ophthalmology.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Algorithms
Artificial Intelligence
Deep Learning
Diagnosis, Computer-Assisted / methods*
Humans
Machine Learning
Precision Medicine / methods