使用自由文本报告管理CANDID-PTX数据集
Curation of the CANDID-PTX Dataset with Free-Text Reports.
作者信息
Feng Sijing, Azzollini Damian, Kim Ji Soo, Jin Cheng-Kai, Gordon Simon P, Yeoh Jason, Kim Eve, Han Mina, Lee Andrew, Patel Aakash, Wu Joy, Urschler Martin, Fong Amy, Simmers Cameron, Tarr Gregory P, Barnard Stuart, Wilson Ben
机构信息
Department of Radiology, Dunedin Hospital, 201 Great King St, Dunedin Central, Dunedin, Otago 9016, New Zealand (S.F., A.F., C.S., B.W.); Eastern Health, Melbourne, Victoria, Australia (D.A.); Auckland District Health Board, Auckland, New Zealand (J.S.K., J.Y., E.K., M.H.); Waitemata District Health Board, Auckland, New Zealand (C.K.J.); Waikato District Health Board, Hamilton, New Zealand (S.P.G.); The University of Auckland Faculty of Medical and Health Sciences, Auckland, Auckland, New Zealand (A.L.); University of Otago Medical School, Dunedin, Otago, New Zealand (A.P.); IBM Almaden Research Center, San Jose, Calif (J.W.); School of Computer Science, University of Auckland, Auckland, New Zealand (M.U.); Department of Radiology, Auckland City Hospital, Auckland, New Zealand (G.P.T.); and Department of Radiology, Middlemore Hospital, Auckland, New Zealand (S.B.).
出版信息
Radiol Artif Intell. 2021 Oct 13;3(6):e210136. doi: 10.1148/ryai.2021210136. eCollection 2021 Nov.
Conventional Radiography, Thorax, Trauma, Ribs, Catheters, Segmentation, Diagnosis, Classification, Supervised Learning, Machine Learning © RSNA, 2021.
传统放射成像、胸部、创伤、肋骨、导管、分割、诊断、分类、监督学习、机器学习 © RSNA，2021 年。
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