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Taxonomy: TH- Dataset analysis/biomathematics: Machine learning techniques
| SU-F-209-3 | Predicting Motion Compensation Errors for CyberKnife SBRT Liver Patients Using a Machine Learning Algorithm M Liu1*, D Granville2 , J E Cygler1,2, E Vandervoort1,2 (1) Carleton University, Ottawa, ON (2) The Ottawa Hospital Cancer Centre, Ottawa, ON |
| SU-I-GPD-T-84 | Using Machine Learning to Predict GI Toxicity in Unresectable Pancreatic Cancer Patients Treated with Stereotactic Body Radiation Therapy T Wu*, S Liauw , University of Chicago Hospitals, Chicago, IL |
| SU-K-DBRA-4 | Evaluating the Linearity of Risk Functions Across Radiotherapy Outcomes Using Deep Learning C Ahern1 , T Pheiffer1*, C Berlind1 , W Lindsay1 , Y Xiao2 , C Simone3 , (1) Oncora Medical, Inc., Philadelphia, PA, (2) University of Pennsylvania, Philadelphia, PA, (3) University of Maryland School of Medicine, Baltimore, Maryland |
| TH-AB-KDBRB1-8 | A Stacking Method for Predicting Patient QA Passing Rates Using Machine Learning D Lam*, T Dvergsten , T Zhao , D Yang , S Mutic , B Sun , Washington University in St Louis, St Louis, MO |
| TU-I345-GePD-F9-2 | Identifying Predictors of Unplanned Hospitalizations After Radiotherapy Using Regularized Survival Models C Ahern1*, T Pheiffer1 , C Berlind1 , W Lindsay1 , Y Xiao2 , C Simone3 , (1) Oncora Medical, Inc., Philadelphia, PA, (2) University of Pennsylvania, Philadelphia, PA, (3) University of Maryland School of Medicine, Baltimore, Maryland |
| TU-I345-GePD-F9-5 | Risk-Index of Colorectal Cancer to Triage for Screening B. Nartowt*, G. Hart , D. Roffman , I. Ali , W. Muhammad , Y. Liang , J. Deng , Yale university School of Medicine, New Haven, CT |
| WE-C1030-GePD-F4-6 | Multi-Classification of Clinical Notes for Natural Language Processing-Based Information Aggregation in Radiotherapy D Ruan*, Y Min , D Low , M Steinberg , UCLA, Los Angeles, CA |
| WE-FG-DBRA-3 | Ensemble Learning: A Case Study with Knowledge Based Treatment Planning J Zhang1*, T Xie2 , Y Sheng3 , Q Wu4 , F Yin5 , Y Ge6 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Durham, NC, (5) Duke University Medical Center, Durham, NC, (6) UNC Charlotte, Charlotte, NC |
| WE-FG-DBRA-7 | Modeling of Multiple Planning Target Volumes (PTVs) in Knowledge-Based Planning (KBP) J Zhang1*, Y Sheng2 , C Wang3 , T Xie4 , F Yin5 , Y Ge6 , Q Wu7 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Center, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Durham, NC, (5) Duke University Medical Center, Durham, NC, (6) UNC Charlotte, Charlotte, NC, (7) Duke University Medical Center, Durham, NC |
| WE-FG-DBRA-9 | Performance Comparison of Knowledge-Based Dose Prediction Techniques A Landers*, R Neph , F Scalzo , D Ruan , K Sheng , UCLA School of Medicine, Los Angeles, CA |
| WE-J-KDBRA1-1 | A Method to Detect Errors in Radiation Therapy Physician Orders Using Association Rules X Chang*, H Li , Y Fu , B Sun , D Yang , Washington University School of Medicine, St Louis, MO |
| WE-J-KDBRA1-6 | Statistical Shape Models for the Automated Detection of OAR Segmentation Abnormalities E Schreibmann*, H Shim , T Liu , N Esiashvili, Emory University, Atlanta, GA |