Artificial Intelligence Systems Assisting Oncologists? Resist and Desist or Enlist and Coexist-Reference-Cited by-同舟云学术

Artificial Intelligence Systems Assisting Oncologists? Resist and Desist or Enlist and Coexist

Published:2019-07-23 Issue:10 Volume:24 Page:1291-1293
ISSN:1083-7159
Container-title:The Oncologist
language:en
Short-container-title:

Author:

Adashek Jacob J.¹,Subbiah Ishwaria M.²,Subbiah Vivek³

Affiliation:

1. Department of Internal Medicine, University of South Florida, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA

2. Division of Cancer Medicine, Department of Palliative, Rehabilitation & Integrative Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA

3. Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA

Abstract

The use of artificial intelligence (AI) has become an integral part of patient care, but there are concerns about the impact of non-human decision assistance on patient outcomes. This commentary focuses on how AI can assist oncologists and benefit patients.

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Oncology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1634/theoncologist.2019-0267

Reference10 articles.

1. The role of clinical trial participation in cancer research: Barriers, evidence, and strategies;Unger;Am Soc Clin Oncol Educ Book,2016

2. Clinically applicable deep learning for diagnosis and referral in retinal disease;De Fauw;Nat Med,2018

3. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography;Ardila;Nat Med,2019

4. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer;Kather;Nat Med,2019

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