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Development of a Novel Deep Learning-Based Prediction Model for the Prognosis of Operable Cervical Cancer.
Dong, Taotao; Wang, Linlin; Li, Ruowen; Liu, Qingqing; Xu, Yiyue; Wei, Yuan; Jiao, Xinlin; Li, Xiaofeng; Zhang, Yida; Zhang, Youzhong; Song, Kun; Yang, Xingsheng; Cui, Baoxia.
Affiliation
  • Dong T; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Wang L; Department of Radiation Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.
  • Li R; Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
  • Liu Q; Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
  • Xu Y; Department of Radiation Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.
  • Wei Y; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Jiao X; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Li X; Cheeloo College of Medicine, Shandong University, Jinan 250012, China.
  • Zhang Y; Shandong University of Traditional Chinese Medicine, Jinan 250335, China.
  • Zhang Y; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Song K; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Yang X; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
  • Cui B; Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250012, China.
Comput Math Methods Med ; 2022: 4364663, 2022.
Article in En | MEDLINE | ID: mdl-36471752
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Uterine Cervical Neoplasms / Deep Learning Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Comput Math Methods Med Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: China Country of publication: United States
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Uterine Cervical Neoplasms / Deep Learning Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Comput Math Methods Med Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: China Country of publication: United States