1.National Multicenter Analysis of Serotype Distribution and Antimicrobial Resistance of Salmonella in China, 2021—2022
Qianqing LI ; Yanan NIU ; Pu QIN ; Honglian WEI ; Jie WANG ; Cuixin QIANG ; Jing YANG ; Zhirong LI ; Weigang WANG ; Min ZHAO ; Qiuyue HUO ; Kaixuan DUAN ; Jianhong ZHAO
Medical Journal of Peking Union Medical College Hospital 2025;16(5):1120-1130
To analyze the distribution of serotypes and antimicrobial resistance of clinical Non-duplicate A total of 605 Clinically isolated
2.Application of support vector machine in the detection of early cancer.
Zhiyong GAO ; Jianya GONG ; Qianqing QIN ; Jiarui LIN
Journal of Biomedical Engineering 2005;22(5):1045-1048
Support Vector Machine (SVM) is an efficient novel method originated from the statistical learning theory. It is powerful in machine learning to solve problems with finite samples. Due to the deficiency of cancer cells, character of patient and noise in the raw data, it is very difficult to diagnose early cancer accurately. In this paper, SVM is employed in detecting early cancer and the results are encouraged compared with conventional methods. The accuracy of Non-linear SVM classifier is especially high in all kinds of classifiers, which indicates the potential application of SVM in early cancer detection.
Algorithms
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Artificial Intelligence
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Data Interpretation, Statistical
;
Early Diagnosis
;
Humans
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Models, Statistical
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Neoplasms
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diagnosis
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Neural Networks (Computer)
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Pattern Recognition, Automated

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