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Keywords: classifier design
PO-GePV-M-39Outcome Prediction of Prostate Cancer Patients After Radiotherapy Using Machine Learning Models Developed with Extrapolation Data
K Oguma1*, T Magome2, M Someya3, T Hasegawa4, K Sakata5, (1) Graduate Division of Health Sciences, Komazawa University, Setagaya, Tokyo, JP, (2) Komazawa University, Tokyo, JP, (3) Department Of Radiology, Sapporo Medical University School Of Medicine, (4) Department Of Radiology, Sapporo Medical University School Of Medicine, (5) Department of Radiology, Sapporo Medical University School Of Medicine
PO-GePV-M-44Classification of Anatomic Structures by CT-Based Radiomics for Head-Neck Radiotherapy
Y Watanabe1*, N Gopishankar2, A Biswas2, K Rangarajan2, G Rath2, (1) University of Minnesota, Minneapolis, MN, (2) All India Institute Of Medical Sciences
SU-IePD-TRACK 2-6Development of Machine Learning Based Algorithm for Prediction of Invasiveness of Early-Lung Adenocarcinoma by Using Chest Computed Tomography
Juyoung Lee1,2*, Seong Yong Park, M.D., Ph.D.3, Jin Sung Kim, Ph.D.1, (1) Department of Radiation Oncology, Yonsei University College of Medicine, Seodaemun-gu, Seoul, KR, (2) Department of Integrative Medicine, Yonsei University College of Medicine, Seoul, KR, (3) Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, KR
TU-IePD-TRACK 6-2Development of a Quantitative Method to Evaluate Organ Segmentation for Enhanced Error Detection
E Pryser*, F Reynoso, M Schmidt, G Hugo, N Knutson, Washington University School of Medicine, St. Louis, MO

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