Comparison of Machine Learning Algorithms and Oversampling Techniques for Urinary Toxicity Prediction After Prostate Cancer Radiotherapy

Pages: 964 - 971
Published: Oct 1, 2019
Abstract
Prostate cancer radiotherapy unavoidably involves the irradiation not only of the target volume, but also of healthy organs-at-risk, neighboring the prostate, likely causing adverse, toxicity-related side-effects. Specifically, in the case of urinary toxicity, these side effects might be associated with a variety of dosimetric, clinical and genetic factors, making its prediction particularly challenging. Given the inconsistency of available data...
Paper Details
Title
Comparison of Machine Learning Algorithms and Oversampling Techniques for Urinary Toxicity Prediction After Prostate Cancer Radiotherapy
Published Date
Oct 1, 2019
Journal
Pages
964 - 971
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