Matthew Li

4.4k total citations
95 papers, 2.6k citations indexed

About

Matthew Li is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Neurology. According to data from OpenAlex, Matthew Li has authored 95 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Oncology and 16 papers in Neurology. Recurrent topics in Matthew Li's work include COVID-19 Clinical Research Studies (11 papers), COVID-19 diagnosis using AI (10 papers) and Long-Term Effects of COVID-19 (9 papers). Matthew Li is often cited by papers focused on COVID-19 Clinical Research Studies (11 papers), COVID-19 diagnosis using AI (10 papers) and Long-Term Effects of COVID-19 (9 papers). Matthew Li collaborates with scholars based in United States, Canada and China. Matthew Li's co-authors include Min Lang, Brent P. Little, Biju Parekkadan, Dexter P. Mendoza, Terry C. Burns, Jayashree Kalpathy–Cramer, Tania Bubela, Avik Som, Harold Atkins and Efrén J. Flores and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Biotechnology and PLoS ONE.

In The Last Decade

Matthew Li

91 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew Li United States 27 585 548 380 379 345 95 2.6k
Shuixing Zhang China 32 2.3k 4.0× 224 0.4× 652 1.7× 319 0.8× 556 1.6× 132 3.8k
Elaine Lee Hong Kong 23 1.9k 3.2× 276 0.5× 613 1.6× 768 2.0× 145 0.4× 110 3.6k
Osamu Sakai Japan 33 1.0k 1.8× 435 0.8× 533 1.4× 98 0.3× 235 0.7× 216 4.0k
Fuhua Yan China 30 2.0k 3.4× 243 0.4× 333 0.9× 803 2.1× 417 1.2× 165 3.8k
Hongyu Wang China 25 466 0.8× 1.3k 2.4× 422 1.1× 202 0.5× 185 0.5× 166 3.8k
Rahul C. Deo United States 30 1.1k 1.9× 2.2k 3.9× 665 1.8× 149 0.4× 433 1.3× 61 7.3k
Takeshi Hara Japan 37 2.2k 3.7× 524 1.0× 733 1.9× 76 0.2× 795 2.3× 327 5.5k
Christine B. Peterson United States 27 513 0.9× 1.2k 2.1× 523 1.4× 164 0.4× 207 0.6× 173 2.8k
Gabriele Cevenini Italy 34 269 0.5× 712 1.3× 509 1.3× 131 0.3× 357 1.0× 212 4.0k
Narges Razavian United States 14 1.2k 2.0× 343 0.6× 371 1.0× 57 0.2× 140 0.4× 39 2.7k

Countries citing papers authored by Matthew Li

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Li

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Li. A scholar is included among the top collaborators of Matthew Li 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 Matthew Li. Matthew Li 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.
Fan, Guixia, Yangyang Shang, Zhi Cao, et al.. (2025). Circular utilization of oilfield wastewater for sustainable flotation separation of coal gasification slag: Advancing waste-to-resource strategies for cleaner production. Journal of Cleaner Production. 520. 146148–146148. 1 indexed citations
2.
3.
Ma, Yue, et al.. (2023). The home language environment and early language ability in rural Southwestern China. Frontiers in Psychology. 13. 1010442–1010442. 9 indexed citations
4.
Li, Matthew, Nishanth Arun, Mehak Aggarwal, et al.. (2022). Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19. Medicine. 101(29). e29587–e29587. 10 indexed citations
5.
Ardestani, Ali, et al.. (2022). External COVID-19 Deep Learning Model Validation on ACR AI-LAB: It’s a Brave New World. Journal of the American College of Radiology. 19(7). 891–900. 3 indexed citations
6.
Lang, Min, Matthew Li, Byung Chul Yoon, et al.. (2021). Severity of Chest Imaging is Correlated with Risk of Acute Neuroimaging Findings among Patients with COVID-19. American Journal of Neuroradiology. 42(5). 831–837. 8 indexed citations
7.
Arun, Nishanth, Nathan Gaw, Praveer Singh, et al.. (2021). Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging. Radiology Artificial Intelligence. 3(6). e200267–e200267. 147 indexed citations
8.
Li, Matthew, et al.. (2021). Artificial intelligence applied to musculoskeletal oncology: a systematic review. Skeletal Radiology. 51(2). 245–256. 23 indexed citations
9.
Nassar, Mahmoud, Nso Nso, Jonathan Ariyaratnam, et al.. (2021). Coronavirus disease 2019 and renal transplantation. World Journal of Clinical Cases. 9(27). 7986–7997. 3 indexed citations
10.
Som, Avik, Min Lang, T. Yeung, et al.. (2020). Implementation of the Radiological Society of North America Expert Consensus Guidelines on Reporting Chest CT Findings Related to COVID-19: A Multireader Performance Study. Radiology Cardiothoracic Imaging. 2(5). e200276–e200276. 24 indexed citations
11.
Li, Matthew, Nishanth Arun, Mishka Gidwani, et al.. (2020). Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs Using Convolutional Siamese Neural Networks. Radiology Artificial Intelligence. 2(4). e200079–e200079. 105 indexed citations
12.
13.
Lang, Min, Avik Som, Denston Carey, et al.. (2020). Pulmonary Vascular Manifestations of COVID-19 Pneumonia. Radiology Cardiothoracic Imaging. 2(3). e200277–e200277. 104 indexed citations
14.
Mehan, William A., Byung Chul Yoon, Min Lang, et al.. (2020). Paraspinal Myositis in Patients with COVID-19 Infection. American Journal of Neuroradiology. 41(10). 1949–1952. 45 indexed citations
15.
Buch, Karen, Byung Chul Yoon, Min Lang, et al.. (2020). Lung apical findings in coronavirus disease (COVID-19) infection on neck and cervical spine CT. Emergency Radiology. 27(6). 731–735. 4 indexed citations
16.
17.
Mukundan, Shilpaa, et al.. (2018). Artificial T Cell Mimetics to Combat Melanoma Tumor Growth. PubMed. 6(1). 21–32. 2 indexed citations
18.
Khong, Danika, et al.. (2018). Stromalized microreactor supports murine hematopoietic progenitor enrichment. Biomedical Microdevices. 20(1). 13–13. 3 indexed citations
19.
Forkert, Nils D., Matthew Li, Robert M. Lober, & Kristen W. Yeom. (2016). Gray Matter Growth Is Accompanied by Increasing Blood Flow and Decreasing Apparent Diffusion Coefficient during Childhood. American Journal of Neuroradiology. 37(9). 1738–1744. 23 indexed citations
20.
Li, Matthew, et al.. (2013). Investigation of Sickle‐Cell Haemoglobin Polymerisation under Electrochemical Control. ChemPhysChem. 14(10). 2143–2148. 2 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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