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Machine learning and medical education
Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools cou...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550167/ https://www.ncbi.nlm.nih.gov/pubmed/31304333 http://dx.doi.org/10.1038/s41746-018-0061-1 |
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author | Kolachalama, Vijaya B. Garg, Priya S. |
author_facet | Kolachalama, Vijaya B. Garg, Priya S. |
author_sort | Kolachalama, Vijaya B. |
collection | PubMed |
description | Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools could play a key role by defining the way medicine will be practiced. Educating the next generation of medical professionals with the right ML techniques will enable them to become part of this emerging data science revolution. |
format | Online Article Text |
id | pubmed-6550167 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65501672019-07-12 Machine learning and medical education Kolachalama, Vijaya B. Garg, Priya S. NPJ Digit Med Perspective Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools could play a key role by defining the way medicine will be practiced. Educating the next generation of medical professionals with the right ML techniques will enable them to become part of this emerging data science revolution. Nature Publishing Group UK 2018-09-27 /pmc/articles/PMC6550167/ /pubmed/31304333 http://dx.doi.org/10.1038/s41746-018-0061-1 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Perspective Kolachalama, Vijaya B. Garg, Priya S. Machine learning and medical education |
title | Machine learning and medical education |
title_full | Machine learning and medical education |
title_fullStr | Machine learning and medical education |
title_full_unstemmed | Machine learning and medical education |
title_short | Machine learning and medical education |
title_sort | machine learning and medical education |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550167/ https://www.ncbi.nlm.nih.gov/pubmed/31304333 http://dx.doi.org/10.1038/s41746-018-0061-1 |
work_keys_str_mv | AT kolachalamavijayab machinelearningandmedicaleducation AT gargpriyas machinelearningandmedicaleducation |