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Advances of Artificial Intelligence Application in Medical Imaging of Ovarian Cancers.
Chen, Xu; Huo, Xiao-Fei; Wu, Zhe; Lu, Jing-Jing.
Afiliación
  • Chen X; Department of Radiology, Beijing United Family Hospital, Beijing 100015, China.
  • Huo XF; Department of Radiology, Beijing United Family Hospital, Beijing 100015, China.
  • Wu Z; Department of Radiology, Fushun Central Hospital, Fushun, Liaoning 113006, China.
  • Lu JJ; Department of Radiology, Beijing United Family Hospital, Beijing 100015, China.
Chin Med Sci J ; 36(3): 196-203, 2021 Sep 30.
Article en En | MEDLINE | ID: mdl-34666872
Ovarian cancer is one of the three most common gynecological cancers in the world, and is regarded as a priority in terms of women's cancer. In the past few years, many researchers have attempted to develop and apply artificial intelligence (AI) techniques to multiple clinical scenarios of ovarian cancer, especially in the field of medical imaging. AI-assisted imaging studies have involved computer tomography (CT), ultrasonography (US), and magnetic resonance imaging (MRI). In this review, we perform a literature search on the published studies that using AI techniques in the medical care of ovarian cancer, and bring up the advances in terms of four clinical aspects, including medical diagnosis, pathological classification, targeted biopsy guidance, and prognosis prediction. Meanwhile, current status and existing issues of the researches on AI application in ovarian cancer are discussed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Ováricas / Inteligencia Artificial Tipo de estudio: Guideline / Prognostic_studies Límite: Female / Humans Idioma: En Revista: Chin Med Sci J Asunto de la revista: TERAPIAS COMPLEMENTARES Año: 2021 Tipo del documento: Article País de afiliación: China Pais de publicación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Ováricas / Inteligencia Artificial Tipo de estudio: Guideline / Prognostic_studies Límite: Female / Humans Idioma: En Revista: Chin Med Sci J Asunto de la revista: TERAPIAS COMPLEMENTARES Año: 2021 Tipo del documento: Article País de afiliación: China Pais de publicación: China