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PSA-Net: Deep learning-based physician style-aware segmentation network for postoperative prostate cancer clinical target volumes.

, , , , , , , , , , , and . Artif. Intell. Medicine, (2021)

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Observational Studies (Paul R. Rosenbaum. Springer-Verlag).. SIAM Rev., 38 (3): 529 (1996)Distinguishing "Missing at Random" and "Missing Completely at Random", and . The American Statistician, 50 (3): 207--213 (1996)ArticleType: research-article / Full publication date: Aug., 1996 / Copyright © 1996 American Statistical Association.A phase I/II trial of hydroxychloroquine in conjunction with radiation therapy and concurrent and adjuvant temozolomide in patients with newly diagnosed glioblastoma multiforme,, , , , , , , , , and 10 other author(s). Autophagy, 10 (8): 1359-1368 (2014)PSA-Net: Deep Learning based Physician Style-Aware Segmentation Network for Post-Operative Prostate Cancer Clinical Target Volume., , , , , , , , , and 2 other author(s). CoRR, (2021)PSA-Net: Deep learning-based physician style-aware segmentation network for postoperative prostate cancer clinical target volumes., , , , , , , , , and 2 other author(s). Artif. Intell. Medicine, (2021)Review Paper: Design and Analysis of Controlled Trials in Naturally Clustered Environments: Implications for Medical Informatics., , and . JAMIA, 9 (3): 230-238 (2002)Multiple imputation for model checking: completed-data plots with missing and latent data, , , , and . Biometrics, 61 (1): 74--85 (2005)Research Paper: A Reliability Study for Evaluating Information Extraction from Radiology Reports., , , and . JAMIA, 6 (2): 143-150 (1999)Measuring agreement in medical informatics reliability studies., and . J. Biomed. Informatics, 35 (2): 99-110 (2002)