World's Best Scientists 2026 revealed!
Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
44
Citations
9533
World Ranking
480
National Ranking
160

Computer Science

D-Index
47
Citations
10546
World Ranking
6416
National Ranking
854

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Yaozong Gao is affiliated with United Imaging Healthcare (China) and has a substantial record of research in medical imaging and AI applications within healthcare. Their work spans fields primarily focused on Medicine and Computer Science, with significant contributions to subfields such as Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Pulmonary and Respiratory Medicine, and Artificial Intelligence.

Their research particularly concentrates on advanced methods in medical imaging analysis, including radiomics, machine learning, and COVID-19 diagnosis supported by artificial intelligence. Key topics include:

  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 diagnosis using AI
  • Medical Imaging and Analysis
  • Medical Image Segmentation Techniques
  • Medical Imaging Techniques and Applications
  • Lung Cancer Diagnosis and Treatment
  • Brain Tumor Detection and Classification

Yaozong Gao has authored numerous papers published in diverse venues, frequently collaborating with notable researchers. Their major publication venues include:

  • UNC Libraries
  • IEEE Transactions on Medical Imaging
  • arXiv (Cornell University)
  • Medical Image Analysis
  • Neuro-Oncology

Their recent notable papers include:

  • "Lung Infection Quantification of COVID-19 in CT Images with Deep Learning" (2020, arXiv)
  • "Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia" (2020, IEEE Transactions on Medical Imaging)
  • "Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT" (2020, IEEE Journal of Biomedical and Health Informatics)
  • "Abnormal lung quantification in chest CT images of COVID-19 patients with deep learning and its application to severity prediction" (2020, Medical Physics)
  • "Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images" (2021, Pattern Recognition)

Frequent collaborators in Gao's research include:

  • Dinggang Shen
  • Feng Shi
  • Fei Shan
  • Ying Wei
  • Xiaohuan Cao

The combination of Gao's work reveals a consistent focus on leveraging computational techniques such as deep learning and feature selection to improve diagnostic accuracy and quantitative analysis in medical imaging, particularly related to pulmonary diseases like COVID-19 and lung cancer.

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Lung Infection Quantification of COVID-19 in CT Images with Deep Learning

    Fei Shan;Yaozong Gao;Jun Wang;Weiya Shi

  • The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge.

    Nicholas Heller;Fabian Isensee;Klaus H. Maier-Hein;Xiaoshuai Hou

  • Large-Scale Screening of COVID-19 from Community Acquired Pneumonia using Infection Size-Aware Classification

    Feng Shi;Liming Xia;Fei Shan;Dijia Wu

  • Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia

    Xi Ouyang;Jiayu Huo;Liming Xia;Fei Shan

  • Fully convolutional networks for multi-modality isointense infant brain image segmentation

    Dong Nie;Li Wang;Yaozong Gao;Dinggang Sken

  • Estimating CT Image From MRI Data Using Structured Random Forest and Auto-Context Model

    Tri Huynh;Yaozong Gao;Jiayin Kang;Li Wang

  • Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching

    Yanrong Guo;Yaozong Gao;Dinggang Shen

  • Estimating CT Image from MRI Data Using 3D Fully Convolutional Networks.

    Dong Nie;Xiaohuan Cao;Yaozong Gao;Li Wang

  • LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

    Li Wang;Yaozong Gao;Feng Shi;Gang Li

  • ASDNet: Attention Based Semi-supervised Deep Networks for Medical Image Segmentation

    Dong Nie;Yaozong Gao;Li Wang;Dinggang Shen

  • Large-scale screening to distinguish between COVID-19 and community-acquired pneumonia using infection size-aware classification.

    Feng Shi;Liming Xia;Fei Shan;Bin Song

  • Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT

    Liang Sun;Zhanhao Mo;Fuhua Yan;Liming Xia

  • Detecting Anatomical Landmarks for Fast Alzheimer’s Disease Diagnosis

    Jun Zhang;Yue Gao;Yaozong Gao;Brent C. Munsell

  • Representation learning: a unified deep learning framework for automatic prostate MR segmentation.

    Shu Liao;Yaozong Gao;Aytekin Oto;Dinggang Shen

  • Segmentation of neonatal brain MR images using patch-driven level sets.

    Li Wang;Feng Shi;Gang Li;Yaozong Gao

  • Abnormal Lung Quantification in Chest CT Images of COVID-19 Patients with Deep Learning and its Application to Severity Prediction.

    Fei Shan;Yaozong Gao;Jun Wang;Weiya Shi

  • Unsupervised deep feature learning for deformable registration of MR brain images

    Guorong Wu;Minjeong Kim;Qian Wang;Yaozong Gao

  • Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images.

    Xiaoming Liu;Quan Yuan;Yaozong Gao;Kelei He

  • Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images.

    Jun Zhang;Mingxia Liu;Le An;Yaozong Gao

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Feng Shi
Feng Shi United Imaging Intelligence (China)
Guorong Wu
Guorong Wu University of North Carolina at Chapel Hill
Qian Wang
Qian Wang Shanghai Jiao Tong University
Gang Li
Gang Li University of North Carolina at Chapel Hill
Dong Nie
Dong Nie University of North Carolina at Chapel Hill
Daoqiang Zhang
Daoqiang Zhang Nanjing University of Aeronautics and Astronautics
Ligang Wu
Ligang Wu Harbin Institute of Technology
Pew Thian Yap
Pew Thian Yap University of North Carolina at Chapel Hill
Klaus H. Maier-Hein
Klaus H. Maier-Hein German Cancer Research Center

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Computer Science opens doors to numerous online degrees and specialized career paths across different fields. If you're looking to expand your expertise, consider degrees closely related to technology, data, and management. Many universities in the USA now offer flexible online options, making it easier to balance studies with work and other commitments.

Cost is often a deciding factor. For students interested in legal technology, the criminal justice degree cost can vary depending on the school and level of study. In the business sector, the accounting degree online cost is another important consideration for those looking to branch out into finance or data analysis.

For careers focused on big data, analytics, or artificial intelligence, the best online data science masters programs can position you for in-demand jobs. Additionally, technology skills are increasingly relevant in fields like construction. The construction management degree prepares graduates for roles at the intersection of tech, project management, and engineering.

Explore these pathways to find the program that best matches your interests, career goals, and budget.

Best Scientists Citing Yaozong Gao

Trending Scientists

Recently Published Articles