COVID-19 pneumonia diagnosis using chest x-ray radiograph and deep learning. - Dalton Griner; Ran Zhang 009; Xin Tie; Chengzhu Zhang; John W. Garrett; Ke Li 033; Guang-Hong Chen (Computer-Aided Diagnosis, 2021)

A Generalizable Artificial Intelligence Model for COVID-19 Classification Task Using Chest X-ray Radiographs: Evaluated Over Four Clinical Datasets with 15, 097 Patients. - Ran Zhang 009; Xin Tie; John W. Garrett; Dalton Griner; Zhihua Qi; Nicholas B. Bevins; Scott B. Reeder; Guang-Hong Chen (CoRR, 2022)

Automatic Personalized Impression Generation for PET Reports Using Large Language Models. - Xin Tie; Muheon Shin; Ali Pirasteh; Nevein Ibrahim; Zachary Huemann; Sharon M. Castellino; Kara M. Kelly; John W. Garrett; Junjie Hu 001; Steve Y. Cho; Tyler J. Bradshaw (CoRR, 2023)

Deep Learning for Longitudinal Gross Tumor Volume Segmentation in MRI-Guided Adaptive Radiotherapy for Head and Neck Cancer. - Xin Tie; Weijie Chen 008; Zachary Huemann; Brayden Schott; Nuohao Liu; Tyler J. Bradshaw (HNTS-MRG@MICCAI, 2024)

Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network. - Xin Tie; Muheon Shin; Changhee Lee; Scott B. Perlman; Zachary Huemann; Amy J. Weisman; Sharon M. Castellino; Kara M. Kelly; Kathleen M. McCarten; Adina L. Alazraki; Junjie Hu 001; Steve Y. Cho; et al. (CoRR, 2024)

Vision-Language Modeling in PET/CT for Visual Grounding of Positive Findings. - Zachary Huemann; Samuel Church; Joshua D. Warner; Daniel Tran; Xin Tie; Alan B. McMillan; Junjie Hu 001; Steve Y. Cho; Meghan G. Lubner; Tyler J. Bradshaw (CoRR, 2025)