REVIEW article
Front. Oncol.
Sec. Gynecological Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1581157
This article is part of the Research TopicRevolutionizing Cancer Care: AI and Technological Advances in Breast and Gynecological OncologyView all 4 articles
Advancements in Artificial Intelligence for Ultrasound Diagnosis of Ovarian Cancer: A Comprehensive Review
Provisionally accepted
- 1Ningbo University, Ningbo, China
- 2Ningbo First Hospital, Ningbo, Zhejiang Province, China
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Ovarian cancer, as a common gynecological malignancy, is often found at an advanced stage clinically. Thus, improving the early diagnosis of ovarian cancer is crucial for the survival rate of patients. Ultrasound examination is the main method for ovarian cancer screening, but it is greatly influenced by the operator's experience and technique, increasing the risk of misdiagnosis and missed diagnosis. Artificial intelligence uses computers to learn from input data and has already made significant progress in image recognition. Applying artificial intelligence to ultrasound diagnosis of ovarian cancer can enhance diagnostic accuracy, providing earlier treatment for patients. This article reviews the current application of artificial intelligence in the ultrasound diagnosis of ovarian cancer, in order to provide a reference for subsequent clinical diagnosis and treatment.
Keywords: artificial intelligence, ultrasound imaging, ovarian cancer, machine learning, deep learning
Received: 21 Feb 2025; Accepted: 28 May 2025.
Copyright: © 2025 Tang, Xu, Hongpen and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Duan Hongpen, Ningbo First Hospital, Ningbo, 315016, Zhejiang Province, China
Shengmin Zhang, Ningbo First Hospital, Ningbo, 315016, Zhejiang Province, China
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