Prediction of chemoresistance in ovarian cancer based on deep learning with pathological images

Funct Integr Genomics. 2026 Apr 10;26(1):80. doi: 10.1007/s10142-026-01857-5.

Leyan Niu^#^{1

2}, Xiang Li^#³, Zhiquan Mao⁴, Fen Fu⁵, Mingjie Wang⁴, Hengbin Zhang⁴, Le Chen⁴, Qing Zhang⁶, Xiaoli Tang⁷, Weiming Lou⁸

¹ The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330031, China.
² School of Stomatology, Nanchang University, Nanchang, 330031, China.
³ Queen Mary School, Jiangxi Medical College, Nanchang University, Nanchang, 330031, China.
⁴ Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang, 330031, China.
⁵ Department of Obstetrics and Gynecology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330031, China.
⁶ Department of Emergency, Jiangxi Maternal and Child Health Hospital, Nanchang Medical College, Nanchang, 330031, China.
⁷ Department of Biochemistry, Jiangxi Medical College, Nanchang University, Nanchang, 330031, China. xltang@ncu.edu.cn.
⁸ The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330031, China. yaofulou@sina.com.

^# Contributed equally.

No abstract available

Keywords: CNN; Machine learning; Ovarian cancer; Platinum resistance; Tumor microenvironment.

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