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Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment.
Chen, Hui; Yang, Bo-Wen; Qian, Le; Meng, Yi-Shuang; Bai, Xiang-Hui; Hong, Xiao-Wei; He, Xin; Jiang, Mei-Jiao; Yuan, Fei; Du, Qin-Wen; Feng, Wei-Wei.
Affiliation
  • Chen H; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Yang BW; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Qian L; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Meng YS; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Bai XH; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Hong XW; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • He X; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Jiang MJ; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Yuan F; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Du QW; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
  • Feng WW; From the Department of Obstetrics and Gynecology (H.C., B.W.Y., L.Q., X.H., M.J.J., Q.W.D., W.W.F.) and Department of Pathology (F.Y.), Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Huangpu District, Shanghai 200025, China; and Philips Research Asia Shanghai,
Radiology ; 304(1): 106-113, 2022 07.
Article in En | MEDLINE | ID: mdl-35412367
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ovarian Neoplasms / Deep Learning Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Middle aged Language: En Journal: Radiology Year: 2022 Type: Article
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ovarian Neoplasms / Deep Learning Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Middle aged Language: En Journal: Radiology Year: 2022 Type: Article