Emily Alsentzer

3.3k total citations · 2 hit papers
22 papers, 1.2k citations indexed

About

Emily Alsentzer is a scholar working on Artificial Intelligence, Health Informatics and Molecular Biology. According to data from OpenAlex, Emily Alsentzer has authored 22 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Health Informatics and 3 papers in Molecular Biology. Recurrent topics in Emily Alsentzer's work include Machine Learning in Healthcare (6 papers), Topic Modeling (5 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Emily Alsentzer is often cited by papers focused on Machine Learning in Healthcare (6 papers), Topic Modeling (5 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Emily Alsentzer collaborates with scholars based in United States, Peru and Canada. Emily Alsentzer's co-authors include Tristan Naumann, Wei‐Hung Weng, Matthew B. A. McDermott, William Boag, John R. Murphy, David W. Bates, Jorge A. Rodriguez, Travis Zack, Leo Anthony Celi and Mirac Süzgün and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Social Science & Medicine.

In The Last Decade

Emily Alsentzer

18 papers receiving 1.1k citations

Hit Papers

Publicly Available Clinical 2019 2026 2021 2023 2019 2023 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emily Alsentzer United States 9 827 333 255 134 109 22 1.2k
Matthew B. A. McDermott United States 12 1.0k 1.2× 327 1.0× 421 1.7× 316 2.4× 154 1.4× 23 1.6k
Sunyang Fu United States 18 521 0.6× 259 0.8× 233 0.9× 115 0.9× 139 1.3× 86 1.1k
William Boag United States 6 715 0.9× 301 0.9× 99 0.4× 83 0.6× 93 0.9× 12 873
Stephen Wu United States 20 781 0.9× 612 1.8× 88 0.3× 82 0.6× 153 1.4× 49 1.3k
Qiang Wei China 13 470 0.6× 374 1.1× 87 0.3× 137 1.0× 83 0.8× 40 1.1k
Hans Moen Finland 11 464 0.6× 333 1.0× 137 0.5× 46 0.3× 78 0.7× 50 824
Tanja Magoč United States 10 383 0.5× 92 0.3× 271 1.1× 132 1.0× 108 1.0× 33 810
Aokun Chen United States 8 405 0.5× 90 0.3× 288 1.1× 135 1.0× 95 0.9× 24 743
James Masanz United States 10 1.3k 1.5× 1.2k 3.5× 63 0.2× 94 0.7× 217 2.0× 13 1.7k

Countries citing papers authored by Emily Alsentzer

Since Specialization
Citations

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

Fields of papers citing papers by Emily Alsentzer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emily Alsentzer

This figure shows the co-authorship network connecting the top 25 collaborators of Emily Alsentzer. A scholar is included among the top collaborators of Emily Alsentzer 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 Emily Alsentzer. Emily Alsentzer 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.
Burkhart, Michael C., et al.. (2025). Synthetic data distillation enables the extraction of clinical information at scale. npj Digital Medicine. 8(1). 267–267. 1 indexed citations
2.
Cui, H. T., Bowen Chen, Jason Fries, et al.. (2025). TIMER: temporal instruction modeling and evaluation for longitudinal clinical records. npj Digital Medicine. 8(1). 577–577.
3.
Alsentzer, Emily, et al.. (2025). Redefining Bias Audits for Generative AI in Health Care. NEJM AI. 2(9). 1 indexed citations
4.
Alsentzer, Emily, et al.. (2025). Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases. npj Digital Medicine. 8(1). 380–380. 3 indexed citations
5.
Alsentzer, Emily, Timothy Keyes, Akshay Swaminathan, et al.. (2025). MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries. PubMed. 31. 388–399.
6.
Rotenstein, Lisa S., B.E. Hardy, Mitchell Tang, et al.. (2025). Patient-Physician Messaging by Race, Ethnicity, Insurance Type, and Preferred Language. JAMA Network Open. 8(10). e2534549–e2534549.
7.
Rodriguez, Jorge A., Emily Alsentzer, & David W. Bates. (2024). Leveraging large language models to foster equity in healthcare. Journal of the American Medical Informatics Association. 31(9). 2147–2150. 16 indexed citations
8.
Zack, Travis, Eric Lehman, Mirac Süzgün, et al.. (2023). Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study. The Lancet Digital Health. 6(1). e12–e22. 222 indexed citations breakdown →
9.
Alsentzer, Emily, et al.. (2023). Simulation of undiagnosed patients with novel genetic conditions. Nature Communications. 14(1). 6403–6403. 4 indexed citations
10.
Beaulieu‐Jones, Brett K., Mauricio F. Villamar, Phil Scordis, et al.. (2023). Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study. The Lancet Digital Health. 5(12). e882–e894. 16 indexed citations
11.
Alsentzer, Emily, et al.. (2023). Zero-shot interpretable phenotyping of postpartum hemorrhage using large language models. npj Digital Medicine. 6(1). 212–212. 30 indexed citations
12.
Balagopalan, Aparna, et al.. (2022). Mitigating the impact of biased artificial intelligence in emergency decision-making. SHILAP Revista de lepidopterología. 2(1). 149–149. 38 indexed citations
13.
Alsentzer, Emily, Samuel G. Finlayson, Michelle M. Li, & Marinka Žitnik. (2020). Subgraph Neural Networks. Neural Information Processing Systems. 33. 8017–8029. 5 indexed citations
14.
Alsentzer, Emily, et al.. (2020). Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting. Emerging infectious diseases. 26(9). 2196–2200. 1 indexed citations
15.
Alsentzer, Emily, et al.. (2020). Assessing 3 Outbreak Detection Algorithms in an Electronic Syndromic Surveillance System in a Resource-Limited Setting. Emerging infectious diseases. 26(9). 2196–2200. 2 indexed citations
16.
Alsentzer, Emily, John R. Murphy, William Boag, et al.. (2019). Publicly Available Clinical. 72–78. 781 indexed citations breakdown →
17.
Hswen, Yulin, Kara Sewalk, Emily Alsentzer, et al.. (2018). Investigating inequities in hospital care among lesbian, gay, bisexual, and transgender (LGBT) individuals using social media. Social Science & Medicine. 215. 92–97. 20 indexed citations
18.
Lichtman, Joshua S., Emily Alsentzer, Daniel D. Sprockett, et al.. (2015). The effect of microbial colonization on the host proteome varies by gastrointestinal location. The ISME Journal. 10(5). 1170–1181. 27 indexed citations
19.
Alsentzer, Emily, et al.. (2015). Monitoring Acute Diarrhea via an Electronic Surveillance System in the Peruvian Navy. Online Journal of Public Health Informatics. 7(1). 1 indexed citations
20.
Alsentzer, Emily, et al.. (2014). An algorithm developed using the Brighton Collaboration case definitions is more efficient for determining diagnostic certainty. Vaccine. 32(28). 3469–3472. 5 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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