Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review
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 influenc...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1581157/full |
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| author | Chenxin Tang Zhenbin Xu Hongpeng Duan Shengmin Zhang |
| author_facet | Chenxin Tang Zhenbin Xu Hongpeng Duan Shengmin Zhang |
| author_sort | Chenxin Tang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-cb66f9aba6184bfc98fe49ca206ce06e |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-cb66f9aba6184bfc98fe49ca206ce06e2025-08-20T03:25:19ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-06-011510.3389/fonc.2025.15811571581157Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive reviewChenxin Tang0Zhenbin Xu1Hongpeng Duan2Shengmin Zhang3Health Science Center, Ningbo University, Ningbo, ChinaDepartment of Ultrasound Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, ChinaDepartment of Ultrasound Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, ChinaDepartment of Ultrasound Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, ChinaOvarian 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.https://www.frontiersin.org/articles/10.3389/fonc.2025.1581157/fullartificial intelligenceultrasound imagingovarian cancermachine learningdeep learning |
| spellingShingle | Chenxin Tang Zhenbin Xu Hongpeng Duan Shengmin Zhang Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review Frontiers in Oncology artificial intelligence ultrasound imaging ovarian cancer machine learning deep learning |
| title | Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review |
| title_full | Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review |
| title_fullStr | Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review |
| title_full_unstemmed | Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review |
| title_short | Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review |
| title_sort | advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer a comprehensive review |
| topic | artificial intelligence ultrasound imaging ovarian cancer machine learning deep learning |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1581157/full |
| work_keys_str_mv | AT chenxintang advancementsinartificialintelligenceforultrasounddiagnosisofovariancanceracomprehensivereview AT zhenbinxu advancementsinartificialintelligenceforultrasounddiagnosisofovariancanceracomprehensivereview AT hongpengduan advancementsinartificialintelligenceforultrasounddiagnosisofovariancanceracomprehensivereview AT shengminzhang advancementsinartificialintelligenceforultrasounddiagnosisofovariancanceracomprehensivereview |