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Hang Yu, MS

Applied Clinical Informatics Branch

Contact InformationNihbc 38A - Lister Hill 10s1021a 301.827.5527

Expertise and Research Interests:

Hang Yu is an image processing engineer at the Lister Hill National Center for Biomedical Communications (LHNCBC), National Library of Medicine (NLM), National Institutes of Health (NIH). He received his MS from University of Missouri - Columbia in 2015. His research interests include machine learning, computer vision, and image analysis.


Karki M, Kantipudi K, Haghighi B, Bui V, Yang F,Yu H, Harris M, Kassim YM, Hurt DE, Rosenthal A, Yaniv Z, Jaeger S. Training Data for Machine Learning to Enhance Patient-Centered Outcomes Research (PCOR) Data Infrastructure — A Case Study in Tuberculosis Drug Resistance.

Yu H, Mohammed FO, Hamid MA, Yang F, Kassim YM, Mohamed AO, Maude RJ, Ding XC, Owusu ED, Yerlikaya S, Dittrich S, Jaeger S . Patient-level performance evaluation of a smartphone-based malaria diagnostic application. Malar J 22, 33 (2023).

Karki M, Kantipudi K, Yang F, Yu H, Wang xY, Yaniv Z, Jaeger S. Generalization Challenges in Drug-Resistant Tuberculosis Detection from Chest X-rays. Diagnostics (Basel). 2022 Jan 13;12(1):188. doi: 10.3390/diagnostics12010188. PMID: 35054355; PMCID: PMC8775073.

Karki M, Kantipudi K, Yu H, Yang F, Kassim Y, Yaniv Z,Jaeger S. Identifying Drug-Resistant Tuberculosis in Chest Radiographs: Evaluation of CNN Architectures and Training Strategies. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, accepted on July 15th, 2021, will be held virtually October 31 – November 4, 2021.

Kassim YM, Yang F, Yu H, Maude RJ, Jaeger S. Diagnosing Malaria Patients with Plasmodium falciparum and vivax Using Deep Learning for Thick Smear Images. Diagnostics (Basel). 2021 Oct 27;11(11):1994. doi: 10.3390/diagnostics11111994. PMID: 34829341; PMCID: PMC8621537.

Ufuktepe DK, Yang F, Kassim YM, Yu H, Maude RJ, Palaniappan K, Jaeger S. Deep Learning-Based Cell Detection and Extraction in Thin Blood Smears for Malaria Diagnosis. 50th Annual IEEE AIPR 2021, held virtually October 12-14, 2021.

Yang F, Yu H, Kantipudi K, Rosenthal A, Hurt DE, Yaniv Z, Jaeger S. Automated Drug-Resistant TB Screening: Importance of Demographic Features and Radiological Findings in Chest X-Ray. 50th Annual IEEE AIPR 2021, held virtually October 12-14, 2021.

Yang F, Yu H, Kantipudi K, Rosenthal A, Hurt D, Antani S, Yaniv ZR, Jaeger S. Differentiating between Drug-Sensitive and Drug-Resistant Tuberculosis with Machine Learning for Clinical and Radiological Features. Quantitative Imaging in Medicine and Surgery, 0(0): 1–16, 2021.

Yu H, Yang F, Rajaraman S, Ersoy I, Moallem G, Poostchi M, Palaniappan K, Antani S, Maude RJ, Jaeger S. Malaria Screener: a smartphone application for automated malaria screening. BMC Infect Dis. 2020 Nov 11;20(1):825. doi: 10.1186/s12879-020-05453-1.

Yu H, Yang F, Silamut R, Maude S, Jaeger S, Antani SK. Automatic Blood Smear Analysis with Artificial Intelligence and Smartphones [Poster]. ASTMH 68th Annual Meeting, Washington DC, Nov. 20-24, 2019.

Yang F, Yu H, Silamut K, Maude RJ, Jaeger S, Antani SK. Parasite Detection in Thick Blood Smears Based on Customized Faster-RCNN. Proceedings of AIPR2019, Washington DC, USA, Oct 15-17, 2019.

Yang F, Yu H, Silamut K, Maude R, Jaeger S, Antani SK. Smartphone-Supported Malaria Diagnosis Based on Deep Learning. Proceedings of 10th Workshop on Machine Learning in Medical Imaging (MLMI 2019) in conjunction with MICCAI, Shenzhen, China, Oct 13-17, 2019.

Yang F, Poostchi M, Yu H, Zhou Z, Silamut K, Yu J, Maude RJ, Jaeger S, Antani S. . Deep learning for smartphone-based malaria parasite detection in thick blood smears. IEEE J Biomed Health Inform. 2020 May;24(5):1427-1438. doi: 10.1109/JBHI.2019.2939121. Epub 2019 Sep 23.

Yang F, Yu H, Poostchi M, Silamut K, Maude RJ, Jaeger S. Smartphone-Supported Automated Malaria Parasite Detection. SIIM conference on Machine Intelligence in Medical Imaging, 2018.

Jaeger S, Antani SK, Rajaraman S, Yang F, Yu H. Malaria Screening: Research into Image Analysis and Deep Learning. Report to the Board of Scientific Counselors September 2018.

Yao S, Yu H, AliAkbarpour H, Seetharaman G, Palaniappan K. EpiX: A 3D Measurement Tool for Heritage, Archeology, and Aerial Photogrammetry. Heritage Preservation, pp. 47-66, 2018.

Moallem G, Poostchi M, Yu H, Palaniappan N, Silamut K, Maude RJ, Hossain Md Amir, Jaeger S, Antani SK, Thoma GR. Detecting and Segmenting White Blood Cells in Microscopy Images of Thin Blood Smears [Poster]. Annual Meeting of the American Society of Tropical Medicine & Hygiene (ASTMH), Poster, 2017.

Moallem G, Jaeger S, Poostchi M, Palaniappan N, Yu H, Silamut K, Maude RJ, Antani SK, Thoma GR. White Blood Cell Detection and Segmentation in Microscopy Images of Thin Blood Smears [Poster]. NIH Research Festival, Poster, 2017.

Jaeger S, Silamut K, Yu H, Poostchi Mohammadabadi M, Ersoy I, Powell A, Liang Z, Hossain M, Antani SK, Palaniappan K, Maude R, Thoma GR. Reducing the Diagnostic Burden of Malaria Using Microscopy Image Analysis and Machine Learning in the Field [Poster]. Annual Meeting of the American Society of Tropical Medicine & Hygiene (ASTMH), Atlanta, USA, 2016.

Zweigenbaum P, Demner-Fushman D, Yu H, Cohen KB. Frontiers of biomedical text mining: current progress. Brief Bioinform. 2007 Sep;8(5):358-75. Epub 2007 Oct 30.