Abstract : The aim of this study is to analyze the lymphocyte dynamics during and after radiotherapy and develop neural network models for predicting Radiation-Induced Lymphopenia (RIL) in Stage III Non-Small Cell Lung Cancer (NSCLC) patients using both dosimetric and non-dosimetric information and compare the predictive power to conventional methods (logistic regression, random forests). 

 
About the speaker: I started my PhD program in 2019 at KAIST, South Korea and I have been working with Dr. Clemens Grassberger since 2020. I developed image reconstruction algorithm for Diffuse Optical Tomograph (DOT) for breast screening, radiographic image registration for whole-body X-ray, Metal Artifact Reduction(MAR) for dental CT images using 3D model of dental structure, advanced iterative CT image reconstruction algorithm using curvature during the master at KAIST. After entering to PhD course, I did research on estimating stopping power using CT image for carbon ion therapy at KAIST. After joining to the Grassberger Lab at MGH, I mainly worked on biostatistics, analyzing CT density changes, and developing neural network prediction model using treatment information for non-small cell lung cancer patients. I am happy to share my research at MGH with you.