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Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review

BACKGROUND: With the accumulation of electronic health records and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no researc...

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Detalles Bibliográficos
Autores principales: Yang, Xinyu, Mu, Dongmei, Peng, Hao, Li, Hua, Wang, Ying, Wang, Ping, Wang, Yue, Han, Siqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069295/
https://www.ncbi.nlm.nih.gov/pubmed/35442195
http://dx.doi.org/10.2196/33799
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author Yang, Xinyu
Mu, Dongmei
Peng, Hao
Li, Hua
Wang, Ying
Wang, Ping
Wang, Yue
Han, Siqi
author_facet Yang, Xinyu
Mu, Dongmei
Peng, Hao
Li, Hua
Wang, Ying
Wang, Ping
Wang, Yue
Han, Siqi
author_sort Yang, Xinyu
collection PubMed
description BACKGROUND: With the accumulation of electronic health records and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of artificial intelligence based on electronic health records in cancer care. OBJECTIVE: The aim of this study was to conduct a review to introduce the current state and limitations of artificial intelligence based on electronic health records of patients with cancer and to summarize the performance of artificial intelligence in mining electronic health records and its impact on cancer care. METHODS: Three databases were systematically searched to retrieve potentially relevant papers published from January 2009 to October 2020. Four principal reviewers assessed the quality of the papers and reviewed them for eligibility based on the inclusion criteria in the extracted data. The summary measures used in this analysis were the number and frequency of occurrence of the themes. RESULTS: Of the 1034 papers considered, 148 papers met the inclusion criteria. Cancer care, especially cancers of female organs and digestive organs, could benefit from artificial intelligence based on electronic health records through cancer emergencies and prognostic estimates, cancer diagnosis and prediction, tumor stage detection, cancer case detection, and treatment pattern recognition. The models can always achieve an area under the curve of 0.7. Ensemble methods and deep learning are on the rise. In addition, electronic medical records in the existing studies are mainly in English and from private institutional databases. CONCLUSIONS: Artificial intelligence based on electronic health records performed well and could be useful for cancer care. Improving the performance of artificial intelligence can help patients receive more scientific-based and accurate treatments. There is a need for the development of new methods and electronic health record data sharing and for increased passion and support from cancer specialists.
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spelling pubmed-90692952022-05-05 Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review Yang, Xinyu Mu, Dongmei Peng, Hao Li, Hua Wang, Ying Wang, Ping Wang, Yue Han, Siqi JMIR Med Inform Review BACKGROUND: With the accumulation of electronic health records and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of artificial intelligence based on electronic health records in cancer care. OBJECTIVE: The aim of this study was to conduct a review to introduce the current state and limitations of artificial intelligence based on electronic health records of patients with cancer and to summarize the performance of artificial intelligence in mining electronic health records and its impact on cancer care. METHODS: Three databases were systematically searched to retrieve potentially relevant papers published from January 2009 to October 2020. Four principal reviewers assessed the quality of the papers and reviewed them for eligibility based on the inclusion criteria in the extracted data. The summary measures used in this analysis were the number and frequency of occurrence of the themes. RESULTS: Of the 1034 papers considered, 148 papers met the inclusion criteria. Cancer care, especially cancers of female organs and digestive organs, could benefit from artificial intelligence based on electronic health records through cancer emergencies and prognostic estimates, cancer diagnosis and prediction, tumor stage detection, cancer case detection, and treatment pattern recognition. The models can always achieve an area under the curve of 0.7. Ensemble methods and deep learning are on the rise. In addition, electronic medical records in the existing studies are mainly in English and from private institutional databases. CONCLUSIONS: Artificial intelligence based on electronic health records performed well and could be useful for cancer care. Improving the performance of artificial intelligence can help patients receive more scientific-based and accurate treatments. There is a need for the development of new methods and electronic health record data sharing and for increased passion and support from cancer specialists. JMIR Publications 2022-04-20 /pmc/articles/PMC9069295/ /pubmed/35442195 http://dx.doi.org/10.2196/33799 Text en ©Xinyu Yang, Dongmei Mu, Hao Peng, Hua Li, Ying Wang, Ping Wang, Yue Wang, Siqi Han. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 20.04.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Yang, Xinyu
Mu, Dongmei
Peng, Hao
Li, Hua
Wang, Ying
Wang, Ping
Wang, Yue
Han, Siqi
Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
title Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
title_full Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
title_fullStr Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
title_full_unstemmed Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
title_short Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
title_sort research and application of artificial intelligence based on electronic health records of patients with cancer: systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069295/
https://www.ncbi.nlm.nih.gov/pubmed/35442195
http://dx.doi.org/10.2196/33799
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