Michael Chung

13.3k total citations · 6 hit papers
64 papers, 7.6k citations indexed

About

Michael Chung is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Infectious Diseases. According to data from OpenAlex, Michael Chung has authored 64 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Radiology, Nuclear Medicine and Imaging, 20 papers in Pulmonary and Respiratory Medicine and 10 papers in Infectious Diseases. Recurrent topics in Michael Chung's work include COVID-19 diagnosis using AI (16 papers), COVID-19 Clinical Research Studies (10 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Michael Chung is often cited by papers focused on COVID-19 diagnosis using AI (16 papers), COVID-19 Clinical Research Studies (10 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Michael Chung collaborates with scholars based in United States, China and Spain. Michael Chung's co-authors include Adam Bernheim, Adam Jacobi, Zahi A. Fayad, Xueyan Mei, Mingqian Huang, Shaolin Li, Kunwei Li, Yang Yang, Hong Shan and Ning Zhang and has published in prestigious journals such as Nucleic Acids Research, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Michael Chung

61 papers receiving 7.4k citations

Hit Papers

CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV) 2017 2026 2020 2023 2020 2020 2017 2020 2020 500 1000 1.5k
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.

  1. CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV)
    2020 1.9k citations Michael Chung, Adam Bernheim et al. Radiology profile →
  2. Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection
    2020 1.7k citations Adam Bernheim, Zahi A. Fayad et al. Radiology profile →
  3. TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions
    2017 1.2k citations Michael Chung et al. profile →
  4. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA - Secondary Publication
    2020 554 citations Michael Chung et al. profile →
  5. Radiological Society of North America Expert Consensus Document on Reporting Chest CT Findings Related to COVID-19: Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA
    2020 490 citations Michael Chung et al. Radiology Cardiothoracic Imaging profile →
  6. Portable chest X-ray in coronavirus disease-19 (COVID-19): A pictorial review
    2020 387 citations Adam Jacobi, Michael Chung et al. Clinical Imaging profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Chung United States 25 3.7k 3.1k 1.3k 1.2k 1.2k 64 7.6k
Hong Shan China 33 2.8k 0.7× 3.6k 1.2× 1.2k 0.9× 1.1k 0.9× 1.9k 1.7× 93 8.5k
Shaolin Li China 27 3.0k 0.8× 2.5k 0.8× 870 0.7× 768 0.6× 557 0.5× 110 6.0k
Xiaoyu Han China 22 1.4k 0.4× 2.2k 0.7× 622 0.5× 797 0.7× 316 0.3× 147 4.4k
Ali Gholamrezanezhad United States 28 1.9k 0.5× 1.5k 0.5× 773 0.6× 750 0.6× 197 0.2× 215 4.7k
Jinghui Dong China 12 733 0.2× 4.7k 1.5× 1.0k 0.8× 679 0.6× 707 0.6× 39 6.9k
Lian Yang China 19 1.3k 0.3× 1.7k 0.5× 599 0.5× 513 0.4× 228 0.2× 71 3.5k
Lei Shi China 33 802 0.2× 7.3k 2.3× 1.4k 1.1× 1.2k 1.0× 2.0k 1.7× 122 12.2k
Kai Han China 17 836 0.2× 2.3k 0.8× 602 0.5× 489 0.4× 463 0.4× 38 4.1k
Elaine Lee Hong Kong 23 1.9k 0.5× 768 0.2× 472 0.4× 613 0.5× 276 0.2× 110 3.6k
Zhe Xu China 24 570 0.2× 4.7k 1.5× 969 0.8× 741 0.6× 920 0.8× 84 7.4k

Countries citing papers authored by Michael Chung

Since Specialization
Citations

This map shows the geographic impact of Michael Chung'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 Michael Chung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Chung more than expected).

Fields of papers citing papers by Michael Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Chung. 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 Michael Chung. The network helps show where Michael Chung may publish in the future.

Co-authorship network of co-authors of Michael Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Chung. A scholar is included among the top collaborators of Michael Chung 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 Michael Chung. Michael Chung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Carlo‐Stella, Carmelo, Michael Chung, Heidi Móciková, et al.. (2023). LOTIS‐5, AN ONGOING PHASE 3 RANDOMIZED STUDY OF LONCASTUXIMAB TESIRINE WITH RITUXIMAB (LONCA‐R) VERSUS IMMUNOCHEMOTHERAPY IN PATIENTS WITH R/R DLBCL. Hematological Oncology. 41(S2). 850–851. 2 indexed citations
2.
Xu, Dongming, Rafael E. de la Hoz, Sharon Steinberger, et al.. (2023). Postoperative CT surveillance in the evaluation of local recurrence after sub-lobar resection of neoplastic lesions of the lung. Clinical Imaging. 106. 110030–110030. 1 indexed citations
3.
Pagano, Andrew, Tam Vu, Eugene A. Berkowitz, et al.. (2022). Evaluation of interstitial lung disease: An algorithmic review using ILD-RADS. Clinical Imaging. 88. 45–52. 1 indexed citations
4.
Chung, Michael, et al.. (2022). Early dietitian referral in lung cancer: use of machine learning. BMJ Supportive & Palliative Care. 14(1). 56–59. 4 indexed citations
5.
Berkowitz, Eugene A., Amita Sharma, Jeanne B. Ackman, et al.. (2021). CT Morphologic Characteristics and Variant Patterns of Interstitial Pulmonary Fibrosis in Systemic Lupus Erythematosus. Radiology Cardiothoracic Imaging. 3(4). e200625–e200625. 12 indexed citations
6.
Gupta, Yogesh Sean, Mark Finkelstein, Sayan Manna, et al.. (2021). Coronary artery calcification in COVID-19 patients: an imaging biomarker for adverse clinical outcomes. Clinical Imaging. 77. 1–8. 18 indexed citations
7.
Pagano, Andrew, Mark Finkelstein, Jessica Overbey, et al.. (2021). Portable Chest Radiography as an Exclusionary Test for Adverse Clinical Outcomes During the COVID-19 Pandemic. CHEST Journal. 160(1). 238–248. 2 indexed citations
8.
Langouët, Maéva, Michael Chung, Heather R. Glatt-Deeley, et al.. (2020). Specific ZNF274 binding interference at SNORD116 activates the maternal transcripts in Prader-Willi syndrome neurons. Human Molecular Genetics. 29(19). 3285–3295. 12 indexed citations
9.
Chung, Michael, Maéva Langouët, Stormy J. Chamberlain, & Gordon Carmichael. (2020). Prader-Willi syndrome: reflections on seminal studies and future therapies. Open Biology. 10(9). 200195–200195. 24 indexed citations
10.
11.
Beasley, Mary Beth, et al.. (2020). Radiographically Progressive Metastatic Pulmonary Calcification in a Three-Time Liver Transplant Recipient Requiring Intraoperative Resuscitation. American Journal of Respiratory and Critical Care Medicine. 203(4). 502–503.
12.
Kwon, Young Joon, Danielle Toussie, Mark Finkelstein, et al.. (2020). Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department. Radiology Artificial Intelligence. 3(2). e200098–e200098. 41 indexed citations
13.
Toussie, Danielle, Nicholas Voutsinas, Mark Finkelstein, et al.. (2020). Clinical and Chest Radiography Features Determine Patient Outcomes in Young and Middle-aged Adults with COVID-19. Radiology. 297(1). E197–E206. 230 indexed citations
14.
Manna, Sayan, Samuel Z. Maron, Danielle Toussie, et al.. (2020). COVID-19: A Multimodality Review of Radiologic Techniques, Clinical Utility, and Imaging Features. Radiology Cardiothoracic Imaging. 2(3). e200210–e200210. 52 indexed citations
15.
Voutsinas, Nicholas, et al.. (2020). Improving Communication Between the Emergency Department and Radiology Department With a Novel Web-Based Tool in an Urban Academic Center. Current Problems in Diagnostic Radiology. 50(3). 293–296. 3 indexed citations
16.
Voutsinas, Nicholas, Danielle Toussie, Adam Jacobi, Adam Bernheim, & Michael Chung. (2020). Incidental CT findings in the lungs in COVID-19 patients presenting with abdominal pain. Clinical Imaging. 67. 1–4. 5 indexed citations
17.
Zhu, Yeqing, Yong Wang, Rowena Yip, et al.. (2020). Visual scoring of aortic valve calcifications on low-dose CT in lung cancer screening. European Radiology. 30(5). 2658–2668. 15 indexed citations
18.
Voutsinas, Nicholas, Aalap Chokshi, Michael Chung, et al.. (2018). Aorto-left atrial fistula diagnosed with computed tomographic angiography: A case report. Clinical Imaging. 50. 235–238.
19.
Chung, Michael, et al.. (2015). Noncanonical Amino Acids to Improve the pH Response of pHLIP Insertion at Tumor Acidity. Angewandte Chemie International Edition. 54(12). 3658–3663. 71 indexed citations
20.
Casas‐Tintó, Sergio, Nianwei Lin, Michael Chung, et al.. (2014). An intergenic regulatory region mediates Drosophila Myc-induced apoptosis and blocks tissue hyperplasia. Oncogene. 34(18). 2385–2397. 19 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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