Healthcare Research




Petuum Healthcare Research builds cutting-edge artificial intelligence and machine learning algorithms to improve clinical outcomes and drive transformation in health care.

Petuum Healthcare Research focuses on building novel deep learning, machine learning, natural language processing and computer vision solutions to unlock unstructured, complex and multi-modal medical data including clinical notes, lab test results and medical images and distill insights therefrom. Petuum Healthcare Research aims at developing predictive models with expert-level accuracy to help doctors make better decisions throughout the patient journey.


SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays

Wei Dai, Joseph Doyle, Xiaodan Liang, Hao Zhang, Nanqing Dong, Yuan Li, Eric P. Xing

On the Automatic Generation of Medical Imaging Reports

Baoyu Jing, Pengtao Xie, Eric P. Xing

Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition

Devendra Singh Sachan, Pengtao Xie, Eric P. Xing

Medical Diagnosis from Laboratory Tests by Combining Generative and Discriminative Learning

Shiyue Zhang, Pengtao Xie, Dong Wang, Eric P. Xing

Towards Automated ICD Coding Using Deep Learning

Haoran Shi, Pengtao Xie, Zhiting Hu, Ming Zhang, Eric P. Xing

Predicting Discharge Medications at Admission Time Based on Deep Learning

Yuan Yang, Pengtao Xie, Xin Gao, Carol Cheng, Christy Li, Hongbao Zhang, Eric P. Xing

Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation

Christy Y. Li, Xiaodan Liang, Zhiting Hu, and Eric Xing