Identifying Biomarkers to Select Patients with Borderline Resectable and Locally Advanced Pancreatic Ductal Adenocarcinoma (BRPC, LAPC) for Radiotherapy (RT)

https://openworks.mdanderson.org/sumexp22/1036/thumbnail.jp

Mathematical Modeling of CA19-9 Normalization in Pancreatic Cancer Patients

https://openworks.mdanderson.org/sumexp21/1077/thumbnail.jp

Predicting Tumor Related Liver Failure in Unresectable Intrahepatic Cholangiocarcinoma Patients through the Development of an Imaging Based Deep Learning Neural Network Model

https://openworks.mdanderson.org/sumexp21/1008/thumbnail.jp

The Role of Radiotherapy In the Management of Massive Intrahepatic Cholangiocarcinoma

https://openworks.mdanderson.org/sumexp21/1005/thumbnail.jp

Analysis and Prediction of Patient Survival After Radiotherapy For Liver Cancer Based On Volumetric Segmental Response and Clinically Relevant Factors

https://openworks.mdanderson.org/sumexp23/1121/thumbnail.jp

Identifying Differences in Spatial Transcriptomics Between Subtypes of Pancreatic Ductal Adenocarcinoma

https://openworks.mdanderson.org/sumexp22/1072/thumbnail.jp

Single-cell transcriptomics of intrahepatic cholangiocarcinoma (iCC) reveals novel tumor epithelial-stromal interactions

https://openworks.mdanderson.org/sumexp21/1093/thumbnail.jp

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

Department of Imaging Physics Radiation Oncology Interventional Radiologyhttps://openworks.mdanderson.org/sumexp22/1136/thumbnail.jp