Zhiyun Xue

Zhiyun Xue, PhD

Computational Health Research Branch

Contact InformationNihbc 38A - Lister Hill 10s-1008 301.827.4939

Expertise and Research Interests:

Dr. Zhiyun (Jaylene) Xue is a Staff Scientist at the Lister Hill National Center for Biomedical Communications (LHC) at the National Library of Medicine (NLM). She obtained her Ph.D. from Lehigh University USA, M.S. and B.S. from Tsinghua University, China. Dr. Xue has been working at LHC since 2006 on a number of medical imaging informatics projects. By applying her knowledge and expertise in the fields of machine learning, image processing, and computer vision to analyze biomedical images in different modalities, Dr. Xue puts her R&D efforts in those projects with the goals of advancing the research in biomedical informatics and data science, assisting clinicians at the point-of-care, improving the health of the people, and addressing the needs of the underserved population.

Honors and Awards:

Dr. Xue received the HHS Ignite Group Award in 2014, the NLM Special Acts/Services Group Award in 2011-2014, 2017- 2021.


Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani SK. Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric chest X-ray images. PLOS Digital Health 3(1): e0000286.

Liang Z, Xue Z, Feng Y, Rajaraman S, Huang JX, Antani SK. Emergency Department Wait Time Forecast based on Semantic and Time Series Patterns in COVID-19 Pandemic. 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Istanbul, Turkiye, 2023, pp. 3067-3072, doi: 10.1109/BIBM58861.2023.10385758.

Mahmoodi E, Xue Z, Rajaraman S, Antani SK. A Study on Reducing Big Data Image Annotation Burden Through Iterative Expert-In-The-Loop Strategy. 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Istanbul, Turkiye, 2023, pp. 3097-3102, doi: 10.1109/BIBM58861.2023.10385356.

Rajaraman S, Yang F, Zamzmi G, Xue Z, Antani S. Can deep adult lung segmentation models generalize to the pediatric population? Expert Systems with Applications, Volume 229, Part A, 2023, 120531, ISSN 0957-4174,