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Progress of Artificial Intelligence in Gynecological Malignant Tumors
Artificial intelligence (AI) is a sort of new technical science which can simulate, extend and expand human intelligence by developing theories, methods and application systems. In the last five years, the application of AI in medical research has become a hot topic in modern science and technology....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751777/ https://www.ncbi.nlm.nih.gov/pubmed/33364831 http://dx.doi.org/10.2147/CMAR.S279990 |
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author | Zhou, Jie Zeng, Zhi Ying Li, Li |
author_facet | Zhou, Jie Zeng, Zhi Ying Li, Li |
author_sort | Zhou, Jie |
collection | PubMed |
description | Artificial intelligence (AI) is a sort of new technical science which can simulate, extend and expand human intelligence by developing theories, methods and application systems. In the last five years, the application of AI in medical research has become a hot topic in modern science and technology. Gynecological malignant tumors involves a wide range of knowledge, and AI can play an important part in these aspects, such as medical image recognition, auxiliary diagnosis, drug research and development, treatment scheme formulation and other fields. The purpose of this paper is to describe the progress of AI in gynecological malignant tumors and discuss some problems in its application. It is believed that AI improves the efficiency of diagnosis, reduces the burden of clinicians, and improves the effect of treatment and prognosis. AI will play an irreplaceable role in the field of gynecological malignant oncology and will promote the development of medicine and further promote the transformation from traditional medicine to precision medicine and preventive medicine. However, there are also some problems in the application of AI in gynecologic malignant tumors. For example, AI, inseparable from human participation, still needs to be more “humanized”, and needs to further protect patients’ privacy and health, improve legal and insurance protection, and further improve according to local ethnic conditions and national conditions. However, it is believed that with the continuous development of AI, especially ensemble classifier, and deep learning will have a profound influence on the future of medical technology, which is a powerful driving force for future medical innovation and reform. |
format | Online Article Text |
id | pubmed-7751777 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-77517772020-12-22 Progress of Artificial Intelligence in Gynecological Malignant Tumors Zhou, Jie Zeng, Zhi Ying Li, Li Cancer Manag Res Review Artificial intelligence (AI) is a sort of new technical science which can simulate, extend and expand human intelligence by developing theories, methods and application systems. In the last five years, the application of AI in medical research has become a hot topic in modern science and technology. Gynecological malignant tumors involves a wide range of knowledge, and AI can play an important part in these aspects, such as medical image recognition, auxiliary diagnosis, drug research and development, treatment scheme formulation and other fields. The purpose of this paper is to describe the progress of AI in gynecological malignant tumors and discuss some problems in its application. It is believed that AI improves the efficiency of diagnosis, reduces the burden of clinicians, and improves the effect of treatment and prognosis. AI will play an irreplaceable role in the field of gynecological malignant oncology and will promote the development of medicine and further promote the transformation from traditional medicine to precision medicine and preventive medicine. However, there are also some problems in the application of AI in gynecologic malignant tumors. For example, AI, inseparable from human participation, still needs to be more “humanized”, and needs to further protect patients’ privacy and health, improve legal and insurance protection, and further improve according to local ethnic conditions and national conditions. However, it is believed that with the continuous development of AI, especially ensemble classifier, and deep learning will have a profound influence on the future of medical technology, which is a powerful driving force for future medical innovation and reform. Dove 2020-12-14 /pmc/articles/PMC7751777/ /pubmed/33364831 http://dx.doi.org/10.2147/CMAR.S279990 Text en © 2020 Zhou et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Review Zhou, Jie Zeng, Zhi Ying Li, Li Progress of Artificial Intelligence in Gynecological Malignant Tumors |
title | Progress of Artificial Intelligence in Gynecological Malignant Tumors |
title_full | Progress of Artificial Intelligence in Gynecological Malignant Tumors |
title_fullStr | Progress of Artificial Intelligence in Gynecological Malignant Tumors |
title_full_unstemmed | Progress of Artificial Intelligence in Gynecological Malignant Tumors |
title_short | Progress of Artificial Intelligence in Gynecological Malignant Tumors |
title_sort | progress of artificial intelligence in gynecological malignant tumors |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751777/ https://www.ncbi.nlm.nih.gov/pubmed/33364831 http://dx.doi.org/10.2147/CMAR.S279990 |
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