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Taxonomy: IM- Dataset Analysis/Biomathematics: Machine learning
| PO-GePV-M-32 | Intrafractional Tumor Motion Prediction Using Surrogates On Pancreatic Cine MRgRT A Guta1*, J Shin2, B Lewis3, Z Ji4, J Kim5, T Kim6, (1) Washington University in St. Louis, St. Louis, MO, (2) Yonsei University College of Medicine, Seoul, ,KR, (3) Washington University School of Medicine in St. Louis, Saint Louis, MO, (4) Washington University St Louis, ,,(5) Yonsei University College of Medicine, Seoul, ,KR, (6) Washington University in St. Louis, Saint Louis, MO |
| PO-GePV-M-44 | Classification 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 |
| PO-GePV-M-45 | Prediction of HPV Status in the Head and Neck Cancer Patient Using CT Derived Radiomic Features: The Impact of CT Scanner R Reiazi1,2*, C Arrowsmith1, M Welch3, F Abbas-aghababazadeh1,C Eles1, T Tadic1,2,3, A Hope1,2,3, S Bratman1,2,3, B Haibe-kains1,2,3,4,4,5,6,(1) Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, (2) Department of Medical Biophysics, University of Toronto, (3) Department of Radiation Oncology, University of Toronto, (4) Ontario Institute for Cancer Research, (5) Department of Computer Science, University of Toronto, (6) Vector Institute |
| PO-GePV-M-49 | The Impact of the COVID-19 Pandemic On Cancer Care in Radiation Oncology S Utkarsh1,2*, S Andrea3,4,5, M Gray6, D Wazer1,2, K Leonard1,2, R Munbodh1,2, (1) Department of Radiation Oncology, Warren Alpert Medical School Of Brown University, Providence, RI, (2) Department of Radiation Oncology, Rhode Island Hospital, Providence, RI, (3) Lifespan Biostatistics Core, Rhode Island Hospital, Providence, RI, (4) VA Portland Health Care System, Portland, OR, (5) OHSU-PSU School of Public Health, Portland, OR, (6) Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Providence, RI |
| SU-IePD-TRACK 2-5 | Evaluation of Computer-Aided Nodule Assessment and Risk Yield (CANARY) in Korean Patients for Prediction of Invasiveness of Early Lung Adenocarcinoma 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 |
| SU-IePD-TRACK 2-6 | Development 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 |