Prospect of artificial intelligence based on electronic medical record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Suehyun | - |
dc.contributor.author | Kim, Hun-Sung | - |
dc.date.accessioned | 2023-06-17T08:41:58Z | - |
dc.date.available | 2023-06-17T08:41:58Z | - |
dc.date.created | 2023-06-17 | - |
dc.date.issued | 2021-09 | - |
dc.identifier.issn | 2287-2892 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/88132 | - |
dc.description.abstract | With the advent of the big data era, the interest of the international community is focusing on increasing the utilization of medical big data. Many hospitals are attempting to increase the efficiency of their operations and patient management by adopting artificial intelligence (AI) technology that enables the use of electronic medical record (EMR) data. EMR includes information about a patient's health history, such as diagnoses, medicines, tests, allergies, immunizations, treatment plans, personalized medical care, and improvement of medical quality and safety. EMR data can also be used for AI-based new drug development. In particular, it is effective to develop AI that can predict the occurrence of specific diseases or provide individualized customized treatments by classifying the individualized characteristics of patients. In order to improve performance of artificial intelligence research using EMR data, standardization and refinement of data are essential. In addition, since EMR data deal with sensitive personal information of patients, it is also vital to protect the patient's privacy. There are already various supports for the use of EMR data in the Korean government, and researchers are encouraged to be proactive. © 2021 The Korean Society of Lipid and Atherosclerosis. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Korean Society of Lipid and Atherosclerosis | - |
dc.relation.isPartOf | Journal of Lipid and Atherosclerosis | - |
dc.title | Prospect of artificial intelligence based on electronic medical record | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.12997/JLA.2021.10.3.282 | - |
dc.identifier.bibliographicCitation | Journal of Lipid and Atherosclerosis, v.10, no.3, pp.282 - 290 | - |
dc.identifier.kciid | ART002756014 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85118501728 | - |
dc.citation.endPage | 290 | - |
dc.citation.startPage | 282 | - |
dc.citation.title | Journal of Lipid and Atherosclerosis | - |
dc.citation.volume | 10 | - |
dc.citation.number | 3 | - |
dc.contributor.affiliatedAuthor | Lee, Suehyun | - |
dc.type.docType | Review | - |
dc.subject.keywordAuthor | Artificial intelligence | - |
dc.subject.keywordAuthor | Big data | - |
dc.subject.keywordAuthor | Efficiency | - |
dc.subject.keywordAuthor | Electronic medical record | - |
dc.subject.keywordAuthor | Organizational | - |
dc.subject.keywordAuthor | Patient-centered care | - |
dc.subject.keywordAuthor | Personalized medicine | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
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