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| MO-I345-GePD-F4-6 | Determining Institutional Plan Quality Metrics for Intracranial Stereotactic Radiosurgery (SRS) for Single-Isocenter Multi-Target (SIMT) Treatments W Taylor1*, W Zoller2 , M Addington3 , J Palmer4 , R Raval5 , N Sebastian6 , D DiCostanzo7 , (1) ,Ohio State University, Columbus, (2) Ohio State University, Columbus, ,(3) Ohio State University, Columbus, ,(4) Ohio State University, Columbus, ,(5) Ohio State University, Columbus, ,(6) Ohio State University, Columbus, ,(7) Ohio State University Medical Center, Columbus, OH |
| PO-GePV-E-1 | Evidence-Based Graduate Program Design with Data Analytics R Khan*, T Mazur , S Mutic , Washington University School of Medicine, St Louis, MO |
| PO-GePV-T-132 | Applying TG-218 Methodology to Large Field VMAT QA Using a Gantry-Resolved EPID-Based Technique P Cardoso1*, Q Wu2 , B Liang3 , R Wei3 , (1) Duke Kunshan University, Kunshan, China, (2) Duke University Medical Center, Durham, NC, (3) Image Processing Center, Beihang University, Beijing, China |
| SU-E-221AB-4 | Machine Learning in IMRT Plan Evaluation A Roy1*, D Cutright2 , M Gopalakrishnan3 , B Mittal3 , (1) The University of Texas at San Antonio, San Antonio, TX, (2) University of Chicago Medicine, Chicago, IL, (3) Northwestern Memorial Hospital, Chicago, IL |
| SU-K-301-3 | Analysis of SBRT Planning and Delivery Incidences Via Customized Process Mapping R McGurk1*, B Mullins1, A Amos1, D Gu1, B Chera1, L Marks1, S Das1, L Mazur1,2,3 1. School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 2. School of Information and Library Science, University of North Carolina, Chapel Hill, NC 3. Carolina Health Informatics Program, University of North Carolina, Chapel Hill, NC |
| TH-A-SAN2-10 | Adaptive Margins with An Early Warning System for Motion-Tracking Errors in Liver SBRT M Liu1*, A Ross2 , J E Cygler1,3,4 , E Vandervoort1,3,4 (1) Department of Physics, Carleton University, Ottawa, ON, Canada (2) Department of Physics, McGill University, Montreal, QC, Canada (3) Department of Medical Physics, The Ottawa Hospital Cancer Centre, Ottawa, ON, Canada (4) Department of Radiology, University of Ottawa, Ottawa, ON, Canada |
| TH-B-SAN2-0 | The Anne and Donald Herbert Distinguished Lectureship in Modern Statistical Modeling M Schipper1*, (1) University of Michigan, Ann Arbor, MI |
| TH-B-SAN2-1 | Introduction M Schipper1*, (1) University of Michigan, Ann Arbor, MI |
| TH-B-SAN2-2 | Individualized and Adaptive Radiation Therapy via Statistical Models M Schipper1*, (1) University of Michigan, Ann Arbor, MI |
| TH-B-SAN2-3 | Q&A M Schipper1*, (1) University of Michigan, Ann Arbor, MI |
| TH-D-302-6 | Image Quality Comparison of Statistical Pixel Angiography and Digital Subtraction Angiography for Radioembolization Procedures E Olguin*, L Rill , Z Zhang , B Geller , University of Florida, Gainesville, FL |
| TU-C1000-GePD-F4-6 | Can IMRT QA Failures Be Predicted? How Complexity Metrics Can Guide the Decision for Replanning Before IMRT QA Has Been Measured E Silverstein1*, D Harrington2 , (1) Mayo Clinic Arizona, Phoenix, AZ, (2) Mayo Clinic Arizona, Phoenix, AZ |
| TU-C1000-GePD-F6-2 | Building Robust Machine Learning Models for Colorectal Cancer Risk Prediction B Nartowt1*, G Hart2 , W Muhammad3 , Y Liang4 , J Deng5 , (1) Yale/New Haven Hospital, New Haven, CT, (2) Yale University, New Haven, CT, (3) Yale School of Medicine, Yale University, New Haven, CT, (4) Medical College of Wisconsin, Milwaukee, WI, (5) Yale Univ. School of Medicine, New Haven, CT |
| TU-C930-GePD-F7-3 | External Validation of 3D Spatial Dose-Response Mapping for Toxicity Subsequent to Pelvic Radiotherapy M Marcello1 , A Kennedy2 , A Haworth3 , L Holloway4,5,6 , J Dowling7,8 , P Greer8,9 , S Gulliford10,11 , D Dearnaley11 , M Sydes12 , E Hall11 , J Denham8,9 , M Ebert1,2*, (1) University Of Western Australia, Perth, Australia,(2) Sir Charles Gairdner Hospital, Perth, Australia,(3) University of Sydney, Camperdown, NSW, Australia, (4) Liverpool Hospital, Sydney, Australia,(5) University of New South Wales, Sydney, Australia,(6) University of Wollongong, Wollongong, ,(7) CSIRO, Brisbane, Australia,(8) University of Newcastle, Newcastle, Australia,(9) Calvary Mater Newcastle, Newcastle, Australia,(10) University College London Hospital, London, London, United Kingdom, (11) Institute for Cancer Research, Sutton, United Kingdom, (12) University College London, London, United Kingdom, |
| TU-E-SAN4-0 | The Integration of AI and Machine Learning in Medical Physics Applications V Kearney1*, M Chan2*, C Cardenas3*, (1) University of California San Francisco, San Francsico, CA, (2) Memorial Sloan Kettering Cancer Center, Basking Ridge, NJ, (3) University of Texas MD Anderson Cancer Center, Houston, TX |
| TU-F115-GePD-F4-1 | A Test of the Hypothesis That the Linear-Quadratic (LQ) Model Parameter Beta Decreases with Increasing Particle Linear Energy Transfer (LET) D Wang*, R Stewart , University of Washington , Seattle, WA |
| TU-HI-SAN1-1 | A Novel Plan-Quality Quantification Method Using K-Nearest-Neighbors Referencing J Zhang1*, Q Wu2 , Y Ge3 , C Wang2 , Y Sheng2 , J Palta2 , J Salama2 , F Yin2 , J Zhang2 , (1) Duke Kunshan University, Kunshan, China, (2) Duke University Medical Center, Durham, NC, (3) University of North Carolina at Charlotte, Charlotte, NC |
| WE-HI-301-7 | Machine Learning for Plan Prediction and Quality in TomoTherapy N Shaheen*, RA BAYLISS , P Hill , B Bednarz , University of Wisconsin, Madison, WI |
