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Keywords: Feature Selection
BReP-SNAP-I-20Evaluation of CT-Based Radiomics Features for Predicting Parameters Measured Using a Pulmonary Function Test
Y Ieko1,2*, N Kadoya1, K Abe1,3, S Tanaka1, H Takagi4, T Kanai5, K Ichiji6, T Yamamoto1, H Ariga2, K Jingu1, (1) Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan, (2) Department of Radiation Oncology, Iwate Medical University School of Medicine, Iwate, Japan, (3) Department of Radiology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan, (4) Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Tohoku University, Sendai, Japan, (5) Department of Radiation Oncology, Yamagata University Faculty of Medicine, Yamagata, Japan, (6) Department of Radiological Imaging and Informatics, Tohoku University Graduate School of Medicine, Sendai, Japan.
BReP-SNAP-M-52Deep Neural Network for Survival Analysis Using Intratumoral Radiomics and Dosiomics in the RTOG 0617 Clinical Trial
S Lee*, H Geng, H Zhong, Y Fan, M Rosen, Y Xiao, University of Pennsylvania, Philadelphia, PA
BReP-SNAP-M-109On the Impact of Image Rotation On Quantitative Textural Features in Radiomics Analysis
H Bagher-Ebadian1*, I Chetty1, (1) Henry Ford Health System, Detroit, MI
PO-GeP-I-147Machine Learning Based On CT Radiomic Features Can Predict Residual Tumor From Radiation Changes in Head and Neck Cancer Patients Treated with Definitive Chemoradiotherapy
E Florez*, T Thomas, C M. Howard, H Khosravi, J Storrs, S Lirette, A Fatemi, University of Mississippi Medical Center, Jackson, MS
PO-GeP-M-180Effect of Using Harmonized Radiomic Features On Predicting Volume of Radiographic Changes Following Stereotactic Body Radiotherapy in Lung
R N Mahon1*, M Ghita1, G D Hugo2, N Kalman3, N Mukhopadhyay1, E Weiss1, (1) Virginia Commonwealth University, Richmond, VA, (2) Washington University School of Medicine, St. Louis, MO, (3) Miami Cancer Institute, Miami, FL.
PO-GeP-M-204Evaluation of MRI Radiomics Feature Robustness Using a Virtual Radiomics Phantom
C Ma*, X Wang, K Qing, N Yue, K Nie, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ
PO-GeP-M-239Identifying Robust Radiomic Features Extracted From Images Generated by 0.35T MR-Linac
R Ericsson-szecsenyi1*, G Zhang2, G Redler2, K Latifi2, V Feygelman2, M Tomaszewski2, E Moros2, (1) University of Lund, (2) H. Lee Moffitt Cancer Center, Tampa, FL
PO-GeP-M-331Predicting Treatment Outcome After Immunotherapy Based On Delta-Radiomic Model in Metastatic Melanoma
X Chen1*, M Zhou1, K Wang2, Z Wang4, Z Zhou4, (1) Xi'an Jiaotong University, Xi'an, Shaanxi, CN, (2) UT Southwestern Medical Center, Dallas, TX, (3) Peking University Cancer Hospital, Beijing, CN, (4) University Of Central Missouri, Warrensburg, Missouri
PO-GeP-M-334Prediction of Uterus Volume Shrinkage for Cervical Cancer Patients During Radiotherapy Using Machine-Learning Approach with Treatment Planning-CT Radiomic Features
M Nakano1*, T Nakamoto2, Y Kumai1, Y Koizumi1, M Sumi1, K Nawa2, T Imae2, Y Yoshioka1, M Oguchi1, (1) Cancer Institute Hospital of JFCR, Koto-ku, Tokyo, JP, (2) The University of Tokyo Hospital, Bunkyo-ku, Tokyo, JP
PO-GeP-M-358Radiomics Feature Robustness Under Different Image Perturbation Combinations and Intensities: A Study On Nasopharyngeal Carcinoma CT Images
J Zhang1, X Teng1*, Z Ma1, T Yu1, S Lam1, F Lee2, K Au2, W Yip2, J Cai1, (1) The Hong Kong Polytechnic University, Hung Hom, Kowloon, HKSAR, (2) Queen Elizabeth Hospital, HKSAR
PO-GeP-M-403To Distinguish Peripheral Lung Cancer and Pulmonary Inflammatory Pseudotumor Using CT-Radiomics Features Extracted From PET/CT Images
C Ma, Y Yin*, Shandong Cancer Hospital and Institute,Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, ShandongCN,
PO-GeP-M-412Unboxing Artificial Intelligence "black-Box" Models - A Novel Heuristic
S Weppler1,2*, H Quon1,2, N Harjai1, C Beers1, L Van Dyke2, C Kirkby1,2,3, C Schinkel1,2, W Smith1,2, (1) University of Calgary, Calgary, AB, CA, (2) Tom Baker Cancer Centre, Calgary, AB, CA, (3) Jack Ady Cancer Centre, Lethbridge, AB, CA.
SU-F-TRACK 1-7The Application of Partial Domain Adaptation Transfer Learning in the Classification of Retinopathy Using OCT Images From Different Datasets
J Wu1*, D Li1, YM Yang2, (1) Shandong Normal University, Jinan, Shandong, CN, (2) UCLA, Los Angeles, CA
TU-CD-TRACK 2-9The Association Between Clinical Factors and Biochemical Outcome for High-Risk Prostate Cancer Patients
L Sun1,2*, H Quon1,2, V Tran1, P Chen2, C Kirkby1,3, W Smith1,2 (1) University of Calgary, Calgary, AB, CA, (2) Tom Baker Cancer Centre, Calgary, AB, CA, (3) Jack Ady Cancer Centre, Lethbridge, AB, CA
TU-EF-TRACK 3-7BEST IN PHYSICS (THERAPY): Insights Into Planning Techniques Mastered by An Autoplanning Robot: Can An AI Planning Agent Be Interpretable and Tractable?
J Zhang1*, C Wang1, Y Sheng1, F Yin1, Y Ge2, Q Wu1, (1) Duke University Medical Center, Durham, NC, (2) The University of North Carolina at Charlotte, Chartlotte, NC
WE-E-TRACK 2-4Classification of LGG Tumor IDH1 Gene Mutation Status Using T2/FLAIR MRI Texture Information
M Safari1, 2*, L Archambault1, 2, A Ameri3, A Fatemi4, M Beigi5, (1) Department of Physics, Universite Laval, Quebec, QC, CA, (2) CHU de Quebec - Universite Laval, Quebec, QC, CA, (3) Department Of Clinical Oncology, Shahidbeheshti University, (4) University of Mississippi Med. Center, Jackson, MS, (5) Novin Medical Radiation Institute, Haft Tir Martyrs Hospital, Tehran, Iran.
WE-E-TRACK 2-6Deciphering Metabolic Features to Target Neuroblastoma Using Machine Learning
R Wang1,2,3*, Y Zhang1,4, P Pachnis4, H Vu4, K Wang1,3, R Deberardinis4, J Wang1,3, (1) Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX. (2) School of Artificial Intelligence, Xidian University, Xi'an, People's Republic of China. (3) Medical Artificial Intelligence and Automation (MAIA) Lab, University of Texas Southwestern Medical Center, Dallas, TX. (4) Children's Research Institute, University of Texas Southwestern Medical Center, Dallas, TX.