Selected Publications [Google Scholar]

* denotes co-first authorship

Open-Ended Clinical Text Generation for Acute Care: Applying Reinforcement Learning with Clinically Grounded Rewards

Minjia Wang*, Luyang Luo*, Sung Eun Kim, Fang Cao, David A Kim, Pranav Rajpurkar

Proceedings of the 7th Conference on Health, Inference, and Learning (CHIL), 2026

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports

Mohammed Baharoon*, Luyang Luo*, Michael Moritz, Abhinav Kumar, Sung Eun Kim, Xiaoman Zhang, Miao Zhu, Mahmoud Hussain Alabbad, Maha Sbayel Alhazmi, Neel P. Mistry, Kent Ryan Kleinschmidt, Brady Chrisler, Sathvik Suryadevara, Sri Sai Dinesh Jaliparthi, Noah Michael Prudlo, Mark David Marino, Jeremy Palacio, Rithvik Akula, Hong-Yu Zhou, Ibrahim Ethem Hamamci, Scott J. Adams, Hassan Rayhan AlOmaish, Pranav Rajpurkar

NEJM AI, 2026

Dataset

A clinical environment simulator for dynamic AI evaluation

Luyang Luo*, Sung Eun Kim*, Xiaoman Zhang, Julius M Kernbach, Roshan Kenia, Julian Acosta, Larry Nathanson, Adrian Haimovich, Adam Rodman, Ethan Goh, Jonathan Chen, Nigam Shah, David Kim, James Zou, Faisal Mahmood, Jakob Kather, Matthew Lungren, Vivek Natarajan, Eric Topol, Pranav Rajpurkar

Nature Medicine, 2026

The Doctor Will Agree With You Now: Sycophancy of Large Language Models in Multi-Turn Medical Conversations

Taeil Matthew Kim*, Luyang Luo*, Sung Eun Kim, Arjun Kumar Manrai, Eric Topol, Pranav Rajpurkar

Workshop on Linguistic Analysis for Health, 2026

Oral Presentation

Evaluation of Large Language Models as Emergency Department Revisit Predictors

Emma Chen*, Luyang Luo*, Fatma Gunturkun, Sraavya Sambara, Rushil Arora, Boyang Tom Jin, Pranav Rajpurkar, David A Kim

Biocomputing 2026: Proceedings of the Pacific Symposium, 2026

Oral Presentation

ED-Explain: Personalized Video Instructions for Patients Discharged from the Emergency Department

Luyang Luo*, Emma Chen*, Xiaoman Zhang, Julian Nicolas Acosta, Boyang Tom Jin, Fatma Gunturkun, Christian Rose, Carl Preiksaitis, Brian Suffoletto, Pranav Rajpurkar, David A Kim

Biocomputing 2026: Proceedings of the Pacific Symposium, 2026

Video

An explainable biomedical foundation model via large-scale concept-enhanced vision-language pre-training

Yuxiang Nie, Sunan He, Yequan Bie, Yihui Wang, Zhixuan Chen, Shu Yang, Zhiyuan Cai, Hongmei Wang, Xi Wang, Luyang Luo, Mingxiang Wu, Xian Wu, Ronald Cheong Kin Chan, Yuk Ming Lau, Yefeng Zheng, Pranav Rajpurkar, Hao Chen

Nature Biomedical Engineering, 2026

A universal foundation model for grounded biomedical image interpretation

Linshan Wu, Yuxiang Nie, Sunan He, Jiaxin Zhuang, Luyang Luo, Tao Li, Zhuoyao Xie, Dexuan Chen, Yinghua Zhao, Neeraj Mahboobani, Varut Vardhanabhuti, Ronald Cheong Kin Chan, Yifan Peng, Pranav Rajpurkar, Hao Chen

Nature Communications, 2026

Towards generalizable AI in medicine via Generalist–Specialist Collaboration

Sunan He, Yuxiang Nie, Hongmei Wang, Shu Yang, Yihui Wang, Zhiyuan Cai, Zhixuan Chen, Yingxue Xu, Linshan Wu, Ngai Shing Cheng, Luyang Luo, Huiling Xiang, Xi Lin, Mingxiang Wu, Yifan Peng, George Shih, Ziyang Xu, Xian Wu, Qiong Wang, Ronald Cheong Kin Chan, Varut Vardhanabhuti, Xiaohui Duan, Winnie Chiu Wing Chu, Yefeng Zheng, Pranav Rajpurkar, Kang Zhang, Hao Chen

Nature Biomedical Engineering, 2026

International retrospective observational study of continual learning for AI on endotracheal tube placement from chest radiographs

Emma Chen, Agustina Saenz, Oishi Banerjee, Henrik Marklund, Xiaoman Zhang, Shreya Johri, Hong-Yu Zhou, Luyang Luo, Subathra Adithan, Kay Wu, Siddhant Dogra, Vijay Janapa Reddi, Dominic Buensalido, Helen Kavnoudias, Roman Kloeckner, Lukas Müller, Emmanuel Salinas-Miranda, Maria José Veloza Vega, Johannes Kolck, Tobias Penzkofer, Daiju Ueda, Shannon L Walston, Armin Alvaro Quispe-Cornejo, Michele Salvagno, Christopher Lee, Jonathan Fournier, Rosa Patricia Castillo, Cibele Luna, Tara Bahramipour, Amanda Zuback, Rickmer Braren, Petra Jiraskova, Yutthaphan Wannasopha, Piyapong Khumrin, Desmond Lim Shi Wei Wei, James Thomas Patrick Decourcy Hallinan, Zhicheng Jiao, Thomas Yi, Juana Maria Plasencia Martinez, Nuria Isabel Casado Alarcon, Franz A Fellner, Julian F Niedermair, Derek Wu, Dongkeun Kim, Johannes Haubold, Lars Heiliger, Daniel Pérez-Chada, Pablo Pratesi, Ryan Cummings, Narges Razavian, Anastasia Oikonomou, William T Tran, Thomas Küstner, Saif Afat, Adrienne N Dula, Justin F Rousseau, Franko Hržić, Michael Fuchsjäger, Pranav Rajpurkar

NEJM AI, 2026

State-of-the-Art Text-prompted Medical Segmentation Models Struggle to Ground Chest CT Findings

Mohammed Baharoon, Luyang Luo*, Michael Moritz, Abhinav Kumar, Sung Eun Kim, Xiaoman Zhang, Miao Zhu, Kent Kleinschmidt, Sri Sai Dinesh Jaliparthi, Sathvik Suryadevara, Rithvik Akula, Mark Marino, Wenhui Lei, Ibrahim Ethem Hamamci, Pranav Rajpurkar

Machine Learning for Healthcare (MLHC), 2025

Best Paper

ReXplain: Translating Radiology into Patient-Friendly Video Reports

Luyang Luo, Jenanan Vairavamurthy, Xiaoman Zhang, Abhinav Kumar, Ramon R. Ter-Oganesyan, Stuart T. Schroff, Dan Shilo, Rydhwana Hossain, Mike Moritz, and Pranav Rajpurkar

AAAI AIMedHeath, 2025

Project Page Video Demos Slides News

A Large Model for Non-invasive and Personalized Management of Breast Cancer from Multiparametric MRI

Luyang Luo, Mingxiang Wu, Mei Li, Yi Xin, Qiong Wang, Varut Vardhanabhuti, Winnie CW Chu, Zhenhui Li, Juan Zhou, Pranav Rajpurkar, and Hao Chen

Nature Communications, 2025

Code
Featured Article

Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions

Luyang Luo, Xi Wang, Yi Lin, Xiaoqi Ma, Andong Tan, Vince Vardhanabhuti, Winnie CW Chu, Kwang-Ting Cheng, Hao Chen

IEEE Reviews in Biomedical Engineering (IEEE RBME), 2025

Learning Robust Medical Image Segmentation from Multi-source Annotations

Yifeng Wang, Luyang Luo*, Mingxiang Wu, Qiong Wang, Hao Chen

Medical Image Analysis, 2025

Medical Image Debiasing by Learning Adaptive Agreement from a Biased Council

Luyang Luo, Xin Huang, Minghao Wang, Zhuoyue Wan, Hao Chen

Medical Image Analysis (MedIA), 2025

Large-scale generative tumor synthesis in computed tomography images for improving tumor recognition

Linshan Wu, Jiaxin Zhuang, Yanning Zhou, Sunan He, Jiabo Ma, Luyang Luo, Xi Wang, Xuefeng Ni, Xiaoling Zhong, Mingxiang Wu, Yinghua Zhao, Xiaohui Duan, Varut Vardhanabhuti, Pranav Rajpurkar, Hao Chen

Nature Communications, 2025

SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition

Shu Yang, Zhiyuan Cai, Luyang Luo, Ning Ma, Shuchang Xu, Hao Chen

IEEE Transactions on Medical Imaging (IEEE TMI), 2025

Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images

Luyang Luo, Yanwen Li*, Huangjing Ling, Pheng-Ann Heng, Hao Chen

IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024

Code

Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Bag-Level Classifier is a Good Instance-Level Teacher

Hongyi Wang, Luyang Luo*, Fang Wang, Ruofeng Tong, Yen-Wei Chen, Hongjie Hu, Lanfen Lin, Hao Chen

IEEE Transactions on Medical Imaging (IEEE TMI), 2024

Code

Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Images

Zhizhong Chai, Luyang Luo*, Huangjing Ling, Pheng-Ann Heng, Hao Chen

IEEE Transactions on Medical Imaging (IEEE TMI), 2024

Code

MICA: Towards Explainable Skin Lesion Diagnosis via Multi-Level Image-Concept Alignment

Yequan Bie, Luyang Luo, Hao Chen

AAAI Conference on Artificial Intelligence (AAAI), 2024

Code

Development and validation of an interpretable model integrating multimodal information for improving ovarian cancer diagnosis

Huiling Xiang*, Yongjie Xiao*, Fang Li, Chunyan Li, Lixian Liu, Tingting Deng, Cuiju Yan, Fengtao Zhou, Xi Wang, Jinjing Ou, Qingguang Lin, Ruixia Hong, Lishu Huang, Luyang Luo, Huangjing Lin, Xi Lin, Hao Chen

Nature Communications, 2024

HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification

Cheng Jin, Luyang Luo, Huangjing Lin, Jun Hou, Hao Chen

IEEE Transactions on Medical Imaging (IEEE TMI), 2024

Scale Federated Learning for Label Set Mismatch in Medical Image Classification

Zhipeng Deng, Luyang Luo, Hao Chen

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023

Code

Triplet Attention and Dual-Pool Contrastive Learning for Clinic-Driven Multi-Label Medical Image Classification

Yuhan Zhang, Luyang Luo, Qi Dou, Pheng-Ann Heng

Medical Image Analysis (MedIA), 2023

Rethinking Annotation Granularity for Overcoming Shortcuts in Deep Learning–based Radiograph Diagnosis: A Multicenter Study

Luyang Luo, Hao Chen, Yongjie Xiao, Yanning Zhou, Xi Wang, Varut Vardhanabhuti, Mingxiang Wu, Chu Han, Zaiyi Liu, Xin Hao Benjamin Fang, Efstratios Tsougenis, Huangjing Lin, Pheng-Ann Heng

Radiology: Artificial Intelligence, 2022

Early Accept

Pseudo Bias-Balanced Learning for Debiased Chest X-ray Classification

Luyang Luo, Dunyuan Xu, Hao Chen, Tien-Tsin Wong, Pheng-Ann Heng

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022

Code Data

OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays

Luyang Luo, Hao Chen*, Yanning Zhou, Huangjing Lin, Pheng-Ann Heng

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021

Code
Oral Presentation

Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images

Yanwen Li*, Luyang Luo*, Huangjing Lin, Hao Chen, Pheng-Ann Heng

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021

Code

Deep Mining External Imperfect Data for Chest X-ray Disease Screening

Luyang Luo, Lequan Yu*, Hao Chen, Quande Liu, Xi Wang, Jiaqi Xu, Pheng-Ann Heng

IEEE Transactions on Medical Imaging (IEEE TMI), 2020

Semi-Supervised Medical Image Classification with Relation-Driven Self-Ensembling Model

Quande Liu, Lequan Yu, Luyang Luo, Qi Dou, Pheng Ann Heng

IEEE Transactions on Medical Imaging (IEEE TMI), 2020

Early Accept

Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis

Luyang Luo, Hao Chen, Xi Wang, Qi Dou, Huangjing Lin, Juan Zhou, Gongjie Li, Pheng-Ann Heng

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019

Weakly Supervised 3D Deep Learning for Breast Cancer Classification and Localization of the Lesions in MR Images

Juan Zhou*, Luyang Luo*, Qi Dou, Hao Chen, Cheng Chen, Gong‐Jie Li, Ze‐Fei Jiang, Pheng‐Ann Heng

Journal of Magnetic Resonance Imaging (JMRI), 2019

Cover Page

Detection of Glaucomatous Optic Neuropathy with Spectral-domain Optical Coherence Tomography: A Retrospective Training and Validation Deep-learning Analysis

An Ran Ran, Carol Y Cheung, Xi Wang, Hao Chen, Luyang Luo, Poemen P Chan, Mandy OM Wong, Robert T Chang, Suria S Mannil, Alvin L Young, Hon-wah Yung, Chi Pui Pang, Pheng-Ann Heng, Clement C Tham

The Lancet Digital Health, 2019

News