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Diagnostic performance of deep learning models on ultrasound images for distinguishing benign from malignant ovarian cysts.

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Bibliographic Details
Title: Diagnostic performance of deep learning models on ultrasound images for distinguishing benign from malignant ovarian cysts.
Authors: Li W; Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai 6 Jiao Tong University School of Medicine, Shanghai Institute of Ultrasound in Medicine, Shanghai, 201306, China., Xia Y; Shuyuan Community Health Service Center, Pudong New District, Shanghai, 201304, China., Li Y; Mudanjiang Medical University, Heilongjiang, 157041, China., Wu X; Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai 6 Jiao Tong University School of Medicine, Shanghai Institute of Ultrasound in Medicine, Shanghai, 201306, China. xing_apple@163.com., Shi L; Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai 6 Jiao Tong University School of Medicine, Shanghai Institute of Ultrasound in Medicine, Shanghai, 201306, China. shilin_love@163.com.
Source: Journal of ovarian research [J Ovarian Res] 2026 Apr 15; Vol. 19 (1). Date of Electronic Publication: 2026 Apr 15.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101474849 Publication Model: Electronic Cited Medium: Internet ISSN: 1757-2215 (Electronic) Linking ISSN: 17572215 NLM ISO Abbreviation: J Ovarian Res Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1757-2215
DOI:10.1186/s13048-026-02090-1