[Preliminary Study on the Identification of Aerobic Vaginitis by Artificial Intelligence Analysis System].

Journal: Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition

PMID: 38645857

Abstract

OBJECTIVE: To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated microscopy in the clinical diagnosis of aerobic vaginitis (AV).

Authors

Linling Ye

（ 610041） Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China.
Fan Yu

Department of Thyroid, Breast and Hernia Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhengqiang Hu

（ 610041） Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China.
Xia Wang

Department of Neurology, The Sixth People's Hospital of Huizhou City, Huizhou, China.
Yuanting Tang

（ 610041） Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China.

Keywords

Algorithms Artificial Intelligence Deep Learning Female Humans Lactobacillus Microscopy ROC Curve Software Vagina Vaginosis, Bacterial

External Resources

View on PubMed Access via DOI PubMed (38645857)

[Preliminary Study on the Identification of Aerobic Vaginitis by Artificial Intelligence Analysis System].

Abstract

Authors

Keywords

External Resources

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