Shan Chen

1.1k total citations · 1 hit paper
9 papers, 231 citations indexed

About

Shan Chen is a scholar working on Artificial Intelligence, Health Informatics and General Health Professions. According to data from OpenAlex, Shan Chen has authored 9 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Health Informatics and 3 papers in General Health Professions. Recurrent topics in Shan Chen's work include Topic Modeling (5 papers), Artificial Intelligence in Healthcare and Education (4 papers) and Machine Learning in Healthcare (3 papers). Shan Chen is often cited by papers focused on Topic Modeling (5 papers), Artificial Intelligence in Healthcare and Education (4 papers) and Machine Learning in Healthcare (3 papers). Shan Chen collaborates with scholars based in United States, Netherlands and Canada. Shan Chen's co-authors include Danielle S. Bitterman, Hugo J.W.L. Aerts, Guergana Savova, Marco Guevara-Vega, Shalini Moningi, Benjamin H. Kann, Raymond H. Mak, Paul J. Catalano, Jack M. Qian and Idalid Franco and has published in prestigious journals such as Journal of the American Medical Informatics Association, npj Digital Medicine and The Lancet Digital Health.

In The Last Decade

Shan Chen

8 papers receiving 226 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.

Large language models to identify social determinants of health in electronic health records

2024 119 citations Marco Guevara-Vega, Shan Chen et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shan Chen United States	5	105	88	39	34	33	9	231
Maxine Mackintosh United Kingdom	5	105 1.0×	124 1.4×	46 1.2×	40 1.2×	28 0.8×	10	314
Shawheen J. Rezaei United States	6	60 0.6×	81 0.9×	39 1.0×	18 0.5×	14 0.4×	26	239
Patrick Weber United Kingdom	8	60 0.6×	142 1.6×	44 1.1×	48 1.4×	45 1.4×	14	301
Zfania Tom Korach United States	7	97 0.9×	74 0.8×	106 2.7×	27 0.8×	45 1.4×	9	294
Betina Idnay United States	9	156 1.5×	130 1.5×	42 1.1×	42 1.2×	35 1.1×	23	327
Ashwin Nayak United States	8	96 0.9×	101 1.1×	37 0.9×	21 0.6×	25 0.8×	9	235
Eric Strong United States	4	103 1.0×	188 2.1×	66 1.7×	20 0.6×	17 0.5×	5	319
Madhumita Sushil United States	9	168 1.6×	116 1.3×	59 1.5×	15 0.4×	25 0.8×	19	294
Cesar A. Gomez-Cabello United States	10	72 0.7×	162 1.8×	54 1.4×	27 0.8×	28 0.8×	34	265
Claudia E. Haupt United States	6	106 1.0×	198 2.3×	76 1.9×	46 1.4×	25 0.8×	24	359

Countries citing papers authored by Shan Chen

Since Specialization

Citations

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

Fields of papers citing papers by Shan Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shan Chen

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Gao, Mingye, Anubodh S. Varshney, Shan Chen, et al.. (2025). The use of large language models to enhance cancer clinical trial educational materials. JNCI Cancer Spectrum. 9(2).

2.

Yoon, Wonjin, Shan Chen, Yanjun Gao, et al.. (2024). LCD benchmark: long clinical document benchmark on mortality prediction for language models. Journal of the American Medical Informatics Association. 32(2). 285–295. 2 indexed citations

3.

Gao, Yanjun, Shan Chen, Dmitriy Dligach, et al.. (2024). Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability. JAMIA Open. 8(1). ooae154–ooae154. 3 indexed citations

4.

Guevara-Vega, Marco, Shan Chen, Spencer A. Thomas, et al.. (2024). Large language models to identify social determinants of health in electronic health records. npj Digital Medicine. 7(1). 6–6. 119 indexed citations breakdown →

5.

Chen, Shan, Marco Guevara-Vega, Shalini Moningi, et al.. (2024). The effect of using a large language model to respond to patient messages. The Lancet Digital Health. 6(6). e379–e381. 49 indexed citations

6.

Gallifant, Jack, Shan Chen, Pedro Moreira, et al.. (2024). Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks. PubMed. 2024. 12448–12465. 2 indexed citations

7.

Chen, Shan, et al.. (2024). Evaluating the ChatGPT family of models for biomedical reasoning and classification. Journal of the American Medical Informatics Association. 31(4). 940–948. 38 indexed citations

8.

Guevara-Vega, Marco, Shan Chen, Shalini Moningi, et al.. (2023). Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes. JCO Clinical Cancer Informatics. 7(7). e2200196–e2200196. 5 indexed citations

9.

Chen, Shan, Marco Guevara-Vega, Nicolás David Ramírez, et al.. (2023). Natural Language Processing to Automatically Extract the Presence and Severity of Esophagitis in Notes of Patients Undergoing Radiotherapy. JCO Clinical Cancer Informatics. 7(7). e2300048–e2300048. 13 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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