Machine learning in medicine: what clinicians should know
With the advent of artificial intelligence (AI), machines are increasingly being used to complete complicated tasks, yielding remarkable results. Machine learning (ML) is the most relevant subset of AI in medicine, which will soon become an integral part of our everyday practice. Therefore, physicia...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/169366 |
| _version_ | 1811693748935983104 |
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| author | Sim, Jordan Zheng Ting Fong, Qi Wei Huang, Weimin Tan, Cher Heng |
| author2 | Lee Kong Chian School of Medicine (LKCMedicine) |
| author_facet | Lee Kong Chian School of Medicine (LKCMedicine) Sim, Jordan Zheng Ting Fong, Qi Wei Huang, Weimin Tan, Cher Heng |
| author_sort | Sim, Jordan Zheng Ting |
| collection | NTU |
| description | With the advent of artificial intelligence (AI), machines are increasingly being used to complete complicated tasks, yielding remarkable results. Machine learning (ML) is the most relevant subset of AI in medicine, which will soon become an integral part of our everyday practice. Therefore, physicians should acquaint themselves with ML and AI, and their role as an enabler rather than a competitor. Herein, we introduce basic concepts and terms used in AI and ML, and aim to demystify commonly used AI/ML algorithms such as learning methods including neural networks/deep learning, decision tree and application domain in computer vision and natural language processing through specific examples. We discuss how machines are already being used to augment the physician's decision-making process, and postulate the potential impact of ML on medical practice and medical research based on its current capabilities and known limitations. Moreover, we discuss the feasibility of full machine autonomy in medicine. |
| first_indexed | 2024-10-01T06:56:37Z |
| format | Journal Article |
| id | ntu-10356/169366 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:56:37Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1693662023-07-23T15:38:21Z Machine learning in medicine: what clinicians should know Sim, Jordan Zheng Ting Fong, Qi Wei Huang, Weimin Tan, Cher Heng Lee Kong Chian School of Medicine (LKCMedicine) Tan Tock Seng Hospital Science::Medicine::Computer applications Algorithms Artificial Intelligence With the advent of artificial intelligence (AI), machines are increasingly being used to complete complicated tasks, yielding remarkable results. Machine learning (ML) is the most relevant subset of AI in medicine, which will soon become an integral part of our everyday practice. Therefore, physicians should acquaint themselves with ML and AI, and their role as an enabler rather than a competitor. Herein, we introduce basic concepts and terms used in AI and ML, and aim to demystify commonly used AI/ML algorithms such as learning methods including neural networks/deep learning, decision tree and application domain in computer vision and natural language processing through specific examples. We discuss how machines are already being used to augment the physician's decision-making process, and postulate the potential impact of ML on medical practice and medical research based on its current capabilities and known limitations. Moreover, we discuss the feasibility of full machine autonomy in medicine. Published version 2023-07-17T01:14:24Z 2023-07-17T01:14:24Z 2023 Journal Article Sim, J. Z. T., Fong, Q. W., Huang, W. & Tan, C. H. (2023). Machine learning in medicine: what clinicians should know. Singapore Medical Journal, 64(2), 91-97. https://dx.doi.org/10.11622/smedj.2021054 0037-5675 https://hdl.handle.net/10356/169366 10.11622/smedj.2021054 34005847 2-s2.0-85152162506 2 64 91 97 en Singapore Medical Journal © 2023 Singapore Medical Journal. Published by Wolters Kluwer - Medknow. This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution‑NonCommercial‑ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non‑commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms application/pdf |
| spellingShingle | Science::Medicine::Computer applications Algorithms Artificial Intelligence Sim, Jordan Zheng Ting Fong, Qi Wei Huang, Weimin Tan, Cher Heng Machine learning in medicine: what clinicians should know |
| title | Machine learning in medicine: what clinicians should know |
| title_full | Machine learning in medicine: what clinicians should know |
| title_fullStr | Machine learning in medicine: what clinicians should know |
| title_full_unstemmed | Machine learning in medicine: what clinicians should know |
| title_short | Machine learning in medicine: what clinicians should know |
| title_sort | machine learning in medicine what clinicians should know |
| topic | Science::Medicine::Computer applications Algorithms Artificial Intelligence |
| url | https://hdl.handle.net/10356/169366 |
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