Prediction of Liver Regeneration Post-Radiotherapy Using Machine Learning and Deep Learning Models

Authors

• Yining Zha, The University of Texas MD Anderson Cancer CenterFollow
• Aashish C. Gupta, The University of Texas MD Anderson Cancer Center
• Guillaume Cazoulat PhD, The University of Texas MD Anderson Cancer Center
• Brian Sandeep De MD, The University of Texas MD Anderson Cancer Center
• Iwan Paolucci PhD, The University of Texas MD Anderson Cancer CenterFollow
• Molly McCulloch PhD, The University of Texas MD Anderson Cancer Center
• Mais M. Al Taie, The University of Texas MD Anderson Cancer Center
• Sireesha Yedururi PhD, The University of Texas MD Anderson Cancer Center
• Eugene J. Koay MD, PhD, The University of Texas MD Anderson Cancer CenterFollow
• Kristy K. Brock PhD, The University of Texas MD Anderson Cancer CenterFollow

Files

Description

• Department of Imaging Physics
• Radiation Oncology
• Interventional Radiology

Keywords

Liver Regeneration; Radiotherapy; Prediction; Machine Learning; Deep Learning

Program Affiliation

Summer Undergraduate Research Program

Recommended Citation

Zha, Yining; Gupta, Aashish C.; Cazoulat, Guillaume PhD; De, Brian Sandeep MD; Paolucci, Iwan PhD; McCulloch, Molly PhD; Al Taie, Mais M.; Yedururi, Sireesha PhD; Koay, Eugene J. MD, PhD; and Brock, Kristy K. PhD, "Prediction of Liver Regeneration Post-Radiotherapy Using Machine Learning and Deep Learning Models" (2022). Summer Experience 2022. 134.
https://openworks.mdanderson.org/sumexp22/134