J Korean Med Assoc.  2019 Mar;62(3):136-139. 10.5124/jkma.2019.62.3.136.

The Role of medical doctor in the era of artificial intelligence

• Seo JB

• KMID: 2441063
• DOI: http://doi.org/10.5124/jkma.2019.62.3.136

Abstract

Recent advances in new technologies such as artificial intelligence, big data, and virtual reality have led to significant innovations in various industries. Artificial intelligence, particularly in applications using deep learning algorithms, has shown performance superior to that of humans in several contexts. Accordingly, many researchers and companies have tried to apply artificial intelligence to the healthcare system, with applications including image interpretation, voice recognition, clinical decision support, risk prediction, drug discovery, medical robotics, and workflow improvement. However, several important technical, ethical, and social barriers must be overcome, such as overfitting, lack of interpretability, privacy, security, and safety. Doctors should be prepared to play a key role in applying artificial intelligence through the full course of development, validation, clinical performance, and monitoring.

Keyword

Artificial intelligence in medicine; Machine learning; Deep learning

MeSH Terms

Artificial Intelligence*
Decision Support Systems, Clinical
Delivery of Health Care
Drug Discovery
Humans
Learning
Machine Learning
Privacy
Robotics
Voice

Reference

1. The Lancet. Artificial intelligence in health care: within touching distance. Lancet. 2018; 390:2739.

2. Beam AL, Kohane IS. Big data and machine learning in health care. JAMA. 2018; 319:1317–1318.

3. LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015; 521:436–444.

4. Noorbakhsh-Sabet N, Zand R, Zhang Y, Abedi V. Artificial intelligence transforms the future of healthcare. Am J Med. 2019; 01. 30. [Epub]. DOI: 10.1016/j.amjmed.2019.01.017.

5. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25:44–56.

6. Lee JG, Jun S, Cho YW, Lee H, Kim GB, Seo JB, Kim N. Deep learning in medical imaging: general overview. Korean J Radiol. 2017; 18:570–584.

7. Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJ. Artificial intelligence in radiology. Nat Rev Cancer. 2018; 18:500–510.

8. Park SH, Do KH, Choi JI, Sim JS, Yang DM, Eo H, Woo H, Lee JM, Jung SE, Oh JH. Principles for evaluating the clinical implementation of novel digital healthcare devices. J Korean Med Assoc. 2018; 61:765–775.

9. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K. The practical implementation of artificial intelligence technologies in medicine. Nat Med. 2019; 25:30–36.