Imaging Examination and Quantitative Detection and Analysis of Gastrointestinal Diseases Based on Data Mining Technology
The medical image storage and transmission system completes the collection, storage, management, diagnosis and information processing of digital medical image information generated from digital medical devices, accumulates a large amount of data resources, and uses these valuable data resources to e...
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| Vydáno v: | Journal of medical systems Ročník 44; číslo 1; s. 31 - 15 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
Springer US
01.01.2020
Springer Nature B.V |
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| ISSN: | 0148-5598, 1573-689X, 1573-689X |
| On-line přístup: | Získat plný text |
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| Abstract | The medical image storage and transmission system completes the collection, storage, management, diagnosis and information processing of digital medical image information generated from digital medical devices, accumulates a large amount of data resources, and uses these valuable data resources to extract corresponding diseases. Diagnostic rules that help improve the accuracy of clinical disease diagnosis have always been the subject of medical research and management. Gastrointestinal diseases are common high-risk digestive diseases. This paper studies the imaging detection and quantitative detection and analysis of gastrointestinal diseases based on data mining, aiming to improve the accuracy of doctors’ clinical diagnosis, reduce the misdiagnosis and misdiagnosis of patients’ diseases, and reduce the burden on patients. With the high computing speed and computational accuracy of the computer, combined with the flexible analysis and judgment ability of the human body, the doctor can help the semi-structured and unstructured diagnosis problems. Experiments demonstrate the effectiveness and robustness of the proposed method. |
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| AbstractList | The medical image storage and transmission system completes the collection, storage, management, diagnosis and information processing of digital medical image information generated from digital medical devices, accumulates a large amount of data resources, and uses these valuable data resources to extract corresponding diseases. Diagnostic rules that help improve the accuracy of clinical disease diagnosis have always been the subject of medical research and management. Gastrointestinal diseases are common high-risk digestive diseases. This paper studies the imaging detection and quantitative detection and analysis of gastrointestinal diseases based on data mining, aiming to improve the accuracy of doctors’ clinical diagnosis, reduce the misdiagnosis and misdiagnosis of patients’ diseases, and reduce the burden on patients. With the high computing speed and computational accuracy of the computer, combined with the flexible analysis and judgment ability of the human body, the doctor can help the semi-structured and unstructured diagnosis problems. Experiments demonstrate the effectiveness and robustness of the proposed method. The medical image storage and transmission system completes the collection, storage, management, diagnosis and information processing of digital medical image information generated from digital medical devices, accumulates a large amount of data resources, and uses these valuable data resources to extract corresponding diseases. Diagnostic rules that help improve the accuracy of clinical disease diagnosis have always been the subject of medical research and management. Gastrointestinal diseases are common high-risk digestive diseases. This paper studies the imaging detection and quantitative detection and analysis of gastrointestinal diseases based on data mining, aiming to improve the accuracy of doctors' clinical diagnosis, reduce the misdiagnosis and misdiagnosis of patients' diseases, and reduce the burden on patients. With the high computing speed and computational accuracy of the computer, combined with the flexible analysis and judgment ability of the human body, the doctor can help the semi-structured and unstructured diagnosis problems. Experiments demonstrate the effectiveness and robustness of the proposed method.The medical image storage and transmission system completes the collection, storage, management, diagnosis and information processing of digital medical image information generated from digital medical devices, accumulates a large amount of data resources, and uses these valuable data resources to extract corresponding diseases. Diagnostic rules that help improve the accuracy of clinical disease diagnosis have always been the subject of medical research and management. Gastrointestinal diseases are common high-risk digestive diseases. This paper studies the imaging detection and quantitative detection and analysis of gastrointestinal diseases based on data mining, aiming to improve the accuracy of doctors' clinical diagnosis, reduce the misdiagnosis and misdiagnosis of patients' diseases, and reduce the burden on patients. With the high computing speed and computational accuracy of the computer, combined with the flexible analysis and judgment ability of the human body, the doctor can help the semi-structured and unstructured diagnosis problems. Experiments demonstrate the effectiveness and robustness of the proposed method. |
| ArticleNumber | 31 |
| Author | Long, Liling Li, Tao |
| Author_xml | – sequence: 1 givenname: Tao surname: Li fullname: Li, Tao organization: Fourth Affiliated Hospital of Guangxi Medical University – sequence: 2 givenname: Liling orcidid: 0000-0003-0464-4906 surname: Long fullname: Long, Liling email: cjrlongliling@163.com organization: First Affiliated Hospital of Guangxi Medical University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31838583$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1155_2022_9405579 crossref_primary_10_3390_bios13070753 crossref_primary_10_1155_2022_3833583 crossref_primary_10_1155_2022_7968756 crossref_primary_10_1155_2022_6439315 crossref_primary_10_1186_s40001_025_02718_w crossref_primary_10_1088_1742_6596_1744_4_042202 |
| Cites_doi | 10.1016/j.compbiomed.2015.10.014 10.1007/s11235-017-0321-4 10.1016/j.ogc.2015.10.007 10.4018/ijkdb.2014010104 10.1016/j.jrid.2016.03.006 10.1007/s10586-017-0881-9 10.4103/0972-3919.172344 10.1016/j.knosys.2016.10.001 10.11569/wcjd.v24.i19.2996 10.1148/radiol.2413050965 10.1016/j.accinf.2016.12.004 10.5120/ijca2016908023 10.1016/j.infrared.2018.04.012 10.1016/j.enbuild.2016.06.055 10.1007/s00603-015-0733-y 10.1016/j.patcog.2019.03.009 10.1016/j.mex.2016.12.002 10.1038/srep24454 10.1016/0375-9474(77)90126-9 10.1109/TLA.2016.7555255 10.1016/j.asoc.2016.08.001 10.1016/j.pop.2017.02.002 10.4103/0366-6999.178019 10.1007/s00521-018-3902-6 10.1093/femsle/fnx206 |
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| Copyright | Springer Science+Business Media, LLC, part of Springer Nature 2019 Journal of Medical Systems is a copyright of Springer, (2019). All Rights Reserved. |
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| DOI | 10.1007/s10916-019-1482-3 |
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| Keywords | Data mining technology Gastrointestinal diseases Quantitative detection and analysis Imaging examination |
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