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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| Veröffentlicht in: | Journal of medical systems Jg. 44; H. 1; S. 31 - 15 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Springer US
01.01.2020
Springer Nature B.V |
| Schlagworte: | |
| ISSN: | 0148-5598, 1573-689X, 1573-689X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | 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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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 0148-5598 1573-689X 1573-689X |
| DOI: | 10.1007/s10916-019-1482-3 |