To develop a method for scoring online cone-beam CT (CBCT)-to-planning CT image feature alignment to inform prostate image-guided radiotherapy (IGRT) decision-making. The feasibility of incorporating volume variation metric thresholds, predictive of delivering planned dose into weighted functions, was investigated.
To describe a Bayesian network (BN) and complementary visualization tool, that aim to support decision-making during online cone-beam computed tomography (CBCT)-based image guide radiotherapy (IGRT) for prostate cancer patients.
The current practice of histopathology review is limited in speed and accuracy. The current diagnostic paradigm does not fully describe the complex and complicated patterns of cancer. To address these needs, we develop an automated and objective system that facilitates a comprehensive and easy information management and decision-making.
The effectiveness of patient decision aids (PtDA) is rarely evaluated in the "real world" where patients vary in their preferences related to decision support.
To determine how Canadian patients use and evaluate our widely available PtDA for early-stage prostate cancer treatment with its 8 components.
The Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial enrolled ~155,000 participants to determine whether certain screening exams reduced mortality from prostate, lung, colorectal, and ovarian cancer.
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