About Us

Keya Medical

Company Overview

Beijing Keya Medical Technology Co., Ltd. (Keya Medical)  is a medical company focused on empowering healthcare with AI-driven quality and productivity innovations. Our team works with over 100 hospitals around the world to develop healthcare tools that increase the efficiency of healthcare delivery.


Who are we?

Our team of data scientists are committed to supplying medical imaging AI expertise and technical capabilities to healthcare organizations around the world through computer vision, machine learning, and natural language processing. Our researchers have earned advanced degrees from prestigious academic institutions including Yale, Cornell, Duke, and University of North Carolina.


Transforming Patient Care

Keya Medical  has established strategic partnerships with well-known medical device manufacturers and medical service providers to jointly develop precision medical products. Our team works to understand workflow, end-user needs, and other human factors in the design of new and innovative AI solutions. In doing so, our team transforms patient care by empowering healthcare providers with AI-powered tools that allow them to gain insight into diagnostics, care processes, treatment variability, and patient outcomes.


Prof. Yujie Zhou

Vice President, An Zhen Hospital, Capital Medical University, Beijing

Professor Yuji Zhou, MD, Ph.D., currently serves as the Vice President and Postdoctoral Station Leader of Beijing Anzhen Hospital affiliated with Capital Medical University. Previously, Dr. Zhou led the Beijing Health System high-level tech talent team construction project. He also served as a leader for the Ministry of Health, forming the “Diagnostic and therapeutic criteria for coronary disease.”

He successively undertook more than 10 projects including the National Natural Science Foundation and the “11th Five-Year Plan” key support projects and obtained 4 intervention admission certificates certified by the Ministry of Health including coronary heart disease, arrhythmia, pacemaker, congenital heart disease and two national admission trainer qualifications for coronary intervention and congenital heart disease.

He currently serves also as:

  • Director of the Chinese Medical Intervention Society Cardiovascular Professional Committee
  • Vice Chairman of the Beijing Cardiovascular Society of the Chinese Medical Association
  • Consultation experts of Central Health Committee
  • President and editor-in-chief of the Journal of Cardiovascular and Pulmonary Diseases
  • Associate editor of Chinese Journal of Interventional Cardiology

Prof. HuaFeng LIU

Ph.D. supervisor
Dr. Liu concentrates his research in biomedical optical imaging, image analysis, and computer vision. Dr. Liu received his undergraduate degree from the Department of Optoelectronic Information Engineering School of Zhejiang University prior to earning a joint doctoral degree in 2001 from China and Japan.

Dr. Liu’s career has earned numerous prestigious awards in the field of computer vision, earning the National Outstanding Youth Science Fund in 2015. Dr. Liu has published more than 20 papers in topic journals, including MICCAI, IPMI, International Conference on Computer Vision, and Computer Vision and Pattern Recognition. Over the past five years, Dr. Liu has published over 20 Science Citation Index (SCI) papers that have been included in MedIA, Progress in Biophysics & Molecular Biology, Journal of the Optical Society of America, and IEEE Journal series.

Dr. Liu has obtained six national invention patents and has earned five international academic awards. Dr. Liu is a 3-time award winner of the IEEE ICIP Best Paper Award. In addition, he received the Best Paper Award from the conference on Information Processing in Medical Imaging and was awarded the Best Paper Award of Statistical Atlases in 2011 for his paper titled Computation Models in the Heart: Imaging and Modeling Challenges.

Prof. William Kongto HAU

Ph.D. supervisor
Dr. Hau received his Ph.D. from LKS Faculty of Medicine, the University of Hong Kong in 2000. Dr. Hau brings over 17 years of experience in intravascular ultrasound, image analysis, catheter technology, pressure guidewire measurement, blood flow reserve fraction detection, and cardiovascular research.

Dr. Hau currently serves as a pioneer in the global cardiovascular disease medical researchers group. In this role, Dr. Hau proposed to use blood flow reserve fraction (FFR) as a guiding standard of cardiovascular coronary intervention. In addition, Dr. Hau has published research papers in the world’s top medical research journals, including Circulation, European Cardiology Journal, and Chest Journal. In addition, he has co-authored publications for cardiovascular-related research books with famous international cardiac surgeons. He serves as the manuscript reviewer of distinguished journals including Circulation, European Cardiology Journal, Chest Journal, Journal of the American College of Cardiology and, Journal of Interventional Cardiology.

Prof. Heye Zhang

Ph.D. supervisor
Dr. Zhang specializes in quantitative analysis and health informatics research. He is driven by the demand for clinical health information and has promoted and developed a series of of techniques for the quantitative analysis of health information.

Dr. Zhang has published 78 academic papers, including 42 SCI research papers. The cumulative impact of these papers exceeds 120, and his work has been cited in scholarly publications over 200 times. Dr. Zhang has applied for and authorized five Chinese invention patents, and was awarded 3rd prize at the Wu Wenjun Artificial Intelligence Science and Technology Innovation Awards.

Dr. Kai Ding

Dr. Kai Ding currently serves as an Assistant Professor and Senior Physicist in the Department of Radiology at John Hopkins Hospital.

Dr. Ding has published over 40 papers in top medical journals, and his work has been cited over 1000 times. Dr. Ding is the Associate Editor for Medical Physics, directed by the American Association of Physicists in Medicine. In 2009, he was awarded the title of Young Scientists of the American Association of radiological Physics.

Recent Publications

DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction.

Guo Z., Bai, J., Lu, Y., et al.
In International Conference on Information Processing in Medical Imaging (IPMI).2019

Automated anatomical labeling of coronary arteries via bidirectional tree LSTMs.

Wu, D., Wang, X., Bai, J., et al.
International Journal of Computer Assisted Radiology and Surgery. 14(2):271-280 .2019

Train a 3D U-Net to segment cranial vasculature in CTA volume without manual annotation.

Chen, X., Lu, Y., Bai, J., et al.
In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI).2018

Invasive Cancer Detection Utilizing Compressed Convolutional Neural Network and Transfer Learning.

Kong, B., Sun, S., Wang, X., et al.
In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI).2018

Integrate Domain Knowledge in Training CNN for Ultrasonography Breast Cancer Diagnosis.

Liu, J., Li, W., Zhao, N., et al.
In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).2018

Hemodynamics analysis of the serial stenotic coronary arteries.

Liu, X., Peng, C., Xia, Y., et al.
Biomedical Engineering Online.16(1).127.2017

Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning.

Hussein, S., Cao, K., Song, Q, et al.
In International Conference on Information Processing in Medical Imaging (IPMI).2017

Cancer Metastasis Detection via Spatially Structured Deep Network.

Kong, B., Wang, X., Li, Z., et al.
In International Conference on Information Processing in Medical Imaging (IPMI).2017

TumorNet: Lung nodule characterization using multi-view Convolutional Neural Network with Gaussian Process.

S. Hussein, R. Gillies, K. Cao, et al.
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI).2017