Donghan M. Yang

2.0k total citations · 1 hit paper
47 papers, 1.1k citations indexed

About

Donghan M. Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Biophysics. According to data from OpenAlex, Donghan M. Yang has authored 47 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Artificial Intelligence and 8 papers in Biophysics. Recurrent topics in Donghan M. Yang's work include AI in cancer detection (9 papers), Cell Image Analysis Techniques (8 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). Donghan M. Yang is often cited by papers focused on AI in cancer detection (9 papers), Cell Image Analysis Techniques (8 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). Donghan M. Yang collaborates with scholars based in United States, China and Germany. Donghan M. Yang's co-authors include Shidan Wang, Guanghua Xiao, Ruichen Rong, Xiaowei Zhan, Yang Xie, John D. Minna, Ignacio I. Wistuba, Junya Fujimoto, Hongyu Liu and Ravinath Kausik and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and Journal of Clinical Investigation.

In The Last Decade

Donghan M. Yang

41 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A critical assessment of using ChatGPT for extracting structured data from clinical notes

2024 101 citations Donghan M. Yang, Ruichen Rong et al. profile →

Peers

Donghan M. Yang

RNMI

PRM

ONCOL

Niels Olson United States

Jana Lipková United States

Bryan He United States

Guy Nir Canada

Iringo Kovacs Netherlands

Bas H. M. van der Velden Netherlands

Meyke Hermsen Netherlands

N. K. Timofeeva Netherlands

Brandon D. Gallas United States

Jue Jiang United States

Niels Olson United States

Donghan M. Yang

370 ×0.7

RNMI

467 ×1.1

132 ×0.7

PRM

83 ×0.6

ONCOL

80 ×0.6

Citations per year, relative to Donghan M. Yang Donghan M. Yang (= 1×) peers Niels Olson

Countries citing papers authored by Donghan M. Yang

Since Specialization

Citations

This map shows the geographic impact of Donghan M. Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Donghan M. Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Donghan M. Yang more than expected).

Fields of papers citing papers by Donghan M. Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Donghan M. Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Donghan M. Yang. The network helps show where Donghan M. Yang may publish in the future.

Co-authorship network of co-authors of Donghan M. Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Donghan M. Yang. A scholar is included among the top collaborators of Donghan M. Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Donghan M. Yang. Donghan M. Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Cheruku, Sreekanth, Donghan M. Yang, Qi Zhou, et al.. (2025). Predicting In-Hospital Acute Kidney Injury after Cardiac Surgery Using Machine Learning. Journal of Cardiothoracic and Vascular Anesthesia. 40(1). 195–203. 1 indexed citations

Wang, Shidan, Ruichen Rong, Zhuo Zhao, et al.. (2024). Cell Segmentation With Globally Optimized Boundaries (CSGO): A Deep Learning Pipeline for Whole-Cell Segmentation in Hematoxylin-and-Eosin–Stained Tissues. Laboratory Investigation. 105(2). 102184–102184. 4 indexed citations

Wang, Laura, Ruichen Rong, Andrew J. Park, et al.. (2024). Assessing disease severity in cutaneous lupus patients using natural language processing: Preliminary data from a cohort study. Journal of the American Academy of Dermatology. 92(4). 894–896. 1 indexed citations

Liu, Jialiang, Donghan M. Yang, Yang Xie, et al.. (2024). Incidence and Prevalence of Atherosclerotic Cardiovascular Disease in Cutaneous Lupus Erythematosus. JAMA Dermatology. 161(2). 175–175. 1 indexed citations

Song, Qing, et al.. (2024). Semantic Guided Matting Net. The Computer Journal. 68(3). 322–330.

Zhu, Zhaopeng, Donghan M. Yang, Xianzhi Song, et al.. (2023). Early Gas Kick Warning Based on Temporal Autoencoder. Energies. 16(12). 4606–4606. 5 indexed citations

Rong, Ruichen, Shidan Wang, Xinyi Zhang, et al.. (2023). Enhanced Pathology Image Quality with Restore–Generative Adversarial Network. American Journal Of Pathology. 193(4). 404–416. 13 indexed citations

Wang, Jianhua, Zhi Yan, Tao Pan, et al.. (2023). Drilling Parameters Multi-Objective Optimization Method Based on PSO-Bi-LSTM. Applied Sciences. 13(21). 11666–11666. 6 indexed citations

Wen, Zhuoyu, Yu-Hsuan Lin, Shidan Wang, et al.. (2023). Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images. Genes. 14(4). 921–921. 4 indexed citations

10.

Wang, Shidan, Ruichen Rong, Donghan M. Yang, et al.. (2023). Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images. Nature Communications. 14(1). 7872–7872. 20 indexed citations

11.

Rong, Ruichen, Danni Luo, Zhuoyu Wen, et al.. (2023). A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization. Modern Pathology. 36(8). 100196–100196. 33 indexed citations

12.

Zheng, Zeyu, et al.. (2023). Real-Time Monitoring Model of PDC Bit Wear Based on GRU Neural Network.

13.

Zhang, Xinyi, Frederico O. Gleber‐Netto, Shidan Wang, et al.. (2023). A Deep Learning Onion Peeling Approach to Measure Oral Epithelium Layer Number. Cancers. 15(15). 3891–3891. 3 indexed citations

14.

Arai, Tatsuya, Donghan M. Yang, James W. Campbell, et al.. (2021). Oxygen-Sensitive MRI: A Predictive Imaging Biomarker for Tumor Radiation Response?. International Journal of Radiation Oncology*Biology*Physics. 110(5). 1519–1529. 22 indexed citations

15.

Shen, Yin, Hongyu Liu, Rong Lü, et al.. (2021). Upfront Brain Treatments Followed by Lung Surgery Improves Survival for Stage IV Non-small Cell Lung Cancer Patients With Brain Metastases: A Large Cohort Analysis. Frontiers in Surgery. 8. 649531–649531. 1 indexed citations

16.

Ci, Bo, Donghan M. Yang, Ling Cai, et al.. (2020). Molecular differences across invasive lung adenocarcinoma morphological subgroups. Translational Lung Cancer Research. 9(4). 1029–1040. 7 indexed citations

17.

Wang, Shidan, Donghan M. Yang, Ruichen Rong, Xiaowei Zhan, & Guanghua Xiao. (2019). Pathology Image Analysis Using Segmentation Deep Learning Algorithms. American Journal Of Pathology. 189(9). 1686–1698. 244 indexed citations

18.

Wang, Shidan, Tao Wang, Lin Yang, et al.. (2019). ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network. EBioMedicine. 50. 103–110. 72 indexed citations

19.

Yang, Donghan M., James E. Huettner, G. Larry Bretthorst, et al.. (2017). Intracellular water preexchange lifetime in neurons and astrocytes. Magnetic Resonance in Medicine. 79(3). 1616–1627. 50 indexed citations

20.

Wang, Yu, Wen Wen, Donghan M. Yang, et al.. (2010). Aluminothermal Reaction Approach for Micro‐/Nanofabrications: Syntheses of In₂O₃ Micro‐/Nanostructures and InN Octahedral Nanoshells. Advanced Materials. 22(13). 1479–1483. 14 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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