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Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration
Most people are now familiar with the concepts of big data, deep learning, machine learning, and artificial intelligence (AI) and have a vague expectation that AI using medical big data can be used to improve the quality of medical care. However, the expectation that big data could change the field...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Endocrine Society
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935779/ https://www.ncbi.nlm.nih.gov/pubmed/31884734 http://dx.doi.org/10.3803/EnM.2019.34.4.349 |
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author | Kim, Hun-Sung Kim, Dai-Jin Yoon, Kun-Ho |
author_facet | Kim, Hun-Sung Kim, Dai-Jin Yoon, Kun-Ho |
author_sort | Kim, Hun-Sung |
collection | PubMed |
description | Most people are now familiar with the concepts of big data, deep learning, machine learning, and artificial intelligence (AI) and have a vague expectation that AI using medical big data can be used to improve the quality of medical care. However, the expectation that big data could change the field of medicine is inconsistent with the current reality. The clinical meaningfulness of the results of research using medical big data needs to be examined. Medical staff needs to be clear about the purpose of AI that utilizes medical big data and to focus on the quality of this data, rather than the quantity. Further, medical professionals should understand the necessary precautions for using medical big data, as well as its advantages. No doubt that someday, medical big data will play an essential role in healthcare; however, at present, it seems too early to actively use it in clinical practice. The field continues to work toward developing medical big data and making it appropriate for healthcare. Researchers should continue to engage in empirical research to ensure that appropriate processes are in place to empirically evaluate the results of its use in healthcare. |
format | Online Article Text |
id | pubmed-6935779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Endocrine Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-69357792020-01-02 Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration Kim, Hun-Sung Kim, Dai-Jin Yoon, Kun-Ho Endocrinol Metab (Seoul) Review Article Most people are now familiar with the concepts of big data, deep learning, machine learning, and artificial intelligence (AI) and have a vague expectation that AI using medical big data can be used to improve the quality of medical care. However, the expectation that big data could change the field of medicine is inconsistent with the current reality. The clinical meaningfulness of the results of research using medical big data needs to be examined. Medical staff needs to be clear about the purpose of AI that utilizes medical big data and to focus on the quality of this data, rather than the quantity. Further, medical professionals should understand the necessary precautions for using medical big data, as well as its advantages. No doubt that someday, medical big data will play an essential role in healthcare; however, at present, it seems too early to actively use it in clinical practice. The field continues to work toward developing medical big data and making it appropriate for healthcare. Researchers should continue to engage in empirical research to ensure that appropriate processes are in place to empirically evaluate the results of its use in healthcare. Korean Endocrine Society 2019-12 2019-12-23 /pmc/articles/PMC6935779/ /pubmed/31884734 http://dx.doi.org/10.3803/EnM.2019.34.4.349 Text en Copyright © 2019 Korean Endocrine Society http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Kim, Hun-Sung Kim, Dai-Jin Yoon, Kun-Ho Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration |
title | Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration |
title_full | Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration |
title_fullStr | Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration |
title_full_unstemmed | Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration |
title_short | Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration |
title_sort | medical big data is not yet available: why we need realism rather than exaggeration |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935779/ https://www.ncbi.nlm.nih.gov/pubmed/31884734 http://dx.doi.org/10.3803/EnM.2019.34.4.349 |
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