Sara G. Murray

1.5k total citations
30 papers, 1.0k citations indexed

About

Sara G. Murray is a scholar working on Public Health, Environmental and Occupational Health, Pathology and Forensic Medicine and Health Informatics. According to data from OpenAlex, Sara G. Murray has authored 30 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Public Health, Environmental and Occupational Health, 5 papers in Pathology and Forensic Medicine and 5 papers in Health Informatics. Recurrent topics in Sara G. Murray's work include Artificial Intelligence in Healthcare and Education (5 papers), Hospital Admissions and Outcomes (4 papers) and Innovations in Medical Education (4 papers). Sara G. Murray is often cited by papers focused on Artificial Intelligence in Healthcare and Education (5 papers), Hospital Admissions and Outcomes (4 papers) and Innovations in Medical Education (4 papers). Sara G. Murray collaborates with scholars based in United States, Austria and Australia. Sara G. Murray's co-authors include Jay L. Degen, Kim M. Baeten, Mark A. Petersen, Catherine Bédard, Katerina Akassoglou, Jae Kyu Ryu, Hans Lassmann, Natacha Le Moan, Thomas J. Deerinck and Mario Merlini and has published in prestigious journals such as New England Journal of Medicine, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Sara G. Murray

29 papers receiving 1.0k citations

Peers

Sara G. Murray

NEURO

RHEUM

IMMUN

PFM

EPIDE

Ryan P. Lee United States

Marc Pawlitzki Germany

Raphaël Schneider Canada

Gabriella Cadoni Italy

Nicolas Guillaume France

Louisa Ho Canada

István Takács Hungary

Timo Uphaus Germany

Ahmed Abdelhak Germany

Raeburn B Forbes United Kingdom

Ryan P. Lee United States

Sara G. Murray

201 ×0.6

NEURO

158 ×0.9

RHEUM

76 ×0.4

IMMUN

76 ×0.5

PFM

123 ×0.8

EPIDE

Citations per year, relative to Sara G. Murray Sara G. Murray (= 1×) peers Ryan P. Lee

Countries citing papers authored by Sara G. Murray

Since Specialization

Citations

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

Fields of papers citing papers by Sara G. Murray

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sara G. Murray. 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 Sara G. Murray. The network helps show where Sara G. Murray may publish in the future.

Co-authorship network of co-authors of Sara G. Murray

This figure shows the co-authorship network connecting the top 25 collaborators of Sara G. Murray. A scholar is included among the top collaborators of Sara G. Murray 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 Sara G. Murray. Sara G. Murray 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

Thombley, Robert, et al.. (2026). Ambient Artificial Intelligence Scribes and Physician Financial Productivity. JAMA Network Open. 9(1). e2553233–e2553233.

Gonias, Steven L., et al.. (2024). Establishing priorities for implementation of large language models in pathology and laboratory medicine. Academic Pathology. 11(1). 100101–100101. 6 indexed citations

Beecy, Ashley, Chris Longhurst, Karandeep Singh, Robert M. Wachter, & Sara G. Murray. (2024). The Chief Health AI Officer — An Emerging Role for an Emerging Technology. NEJM AI. 1(7). 7 indexed citations

Hasan, Alifia, Katherine C. Kellogg, William Ratliff, et al.. (2024). Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities. SHILAP Revista de lepidopterología. 3(5). e0000390–e0000390. 22 indexed citations

Sanborn, D. M., et al.. (2023). Gender Disparities in Critical Care Procedure Training of Internal Medicine Residents. ATS Scholar. 4(2). 164–176. 8 indexed citations

Neinstein, Aaron, et al.. (2023). Large Language Models and Medical Education: Preparing for a Rapid Transformation in How Trainees Will Learn to be Doctors. ATS Scholar. 4(3). 282–292. 15 indexed citations

Zack, Travis, et al.. (2022). A Clinical Reasoning-Encoded Case Library Developed through Natural Language Processing. Journal of General Internal Medicine. 38(1). 5–11. 4 indexed citations

Somani, Sulaiman, et al.. (2021). Health Equity in Artificial Intelligence and Primary Care Research: Protocol for a Scoping Review. JMIR Research Protocols. 10(9). e27799–e27799. 11 indexed citations

Soleimani, Hossein, et al.. (2021). Automating Measurement of Trainee Work Hours. Journal of Hospital Medicine. 16(7). 404–408. 7 indexed citations

10.

Lin, Joseph A., Logan Pierce, Sara G. Murray, et al.. (2021). Estimation of Surgical Resident Duty Hours and Workload in Real Time Using Electronic Health Record Data. Journal of surgical education. 78(6). e232–e238. 6 indexed citations

11.

Lester, Will, et al.. (2019). Symptomology Associated with in Utero Exposures to Polysubstance in an Appalachian Population.. SHILAP Revista de lepidopterología. 5(2). 39–39. 3 indexed citations

12.

Monash, Bradley, et al.. (2018). Decreasing Incidence of Postinsulin Hypoglycemia for Hyperkalemia Treatment. Diabetes. 67(Supplement_1). 1 indexed citations

13.

Murray, Sara G., Anand Avati, Gabriela Schmajuk, & Jinoos Yazdany. (2018). Automated and flexible identification of complex disease: building a model for systemic lupus erythematosus using noisy labeling. Journal of the American Medical Informatics Association. 26(1). 61–65. 28 indexed citations

14.

Werthammer, Joseph, et al.. (2017). A management strategy that reduces NICU admissions and decreases charges from the front line of the neonatal abstinence syndrome epidemic. Journal of Perinatology. 37(10). 1108–1111. 18 indexed citations

15.

Murray, Sara G., et al.. (2016). An Atypical Withdrawal Syndrome in Neonates Prenatally Exposed to Gabapentin and Opioids. The Journal of Pediatrics. 181. 286–288. 31 indexed citations

16.

Murray, Sara G., Gabriela Schmajuk, Laura Trupin, et al.. (2016). National Lupus Hospitalization Trends Reveal Rising Rates of Herpes Zoster and Declines in Pneumocystis Pneumonia. PLoS ONE. 11(1). e0144918–e0144918. 34 indexed citations

17.

Ryu, Jae Kyu, Mark A. Petersen, Sara G. Murray, et al.. (2015). Blood coagulation protein fibrinogen promotes autoimmunity and demyelination via chemokine release and antigen presentation. Nature Communications. 6(1). 8164–8164. 216 indexed citations

18.

Murray, Sara G., Gabriela Schmajuk, Laura Trupin, et al.. (2014). A Population‐Based Study of Infection‐Related Hospital Mortality in Patients With Dermatomyositis/Polymyositis. Arthritis Care & Research. 67(5). 673–680. 37 indexed citations

19.

Murray, Sara G., Jinoos Yazdany, Rachel Kaiser, et al.. (2012). Cardiovascular disease and cognitive dysfunction in systemic lupus erythematosus. Arthritis Care & Research. 64(9). 1328–1333. 50 indexed citations

20.

Davalos, Dimitrios, Jae Kyu Ryu, Mario Merlini, et al.. (2012). Fibrinogen-induced perivascular microglial clustering is required for the development of axonal damage in neuroinflammation. Nature Communications. 3(1). 1227–1227. 432 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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