Suresh Balu

2.2k total citations
54 papers, 1.1k citations indexed

About

Suresh Balu is a scholar working on Health Informatics, Artificial Intelligence and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Suresh Balu has authored 54 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Health Informatics, 17 papers in Artificial Intelligence and 15 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Suresh Balu's work include Artificial Intelligence in Healthcare and Education (19 papers), Machine Learning in Healthcare (16 papers) and Health Systems, Economic Evaluations, Quality of Life (7 papers). Suresh Balu is often cited by papers focused on Artificial Intelligence in Healthcare and Education (19 papers), Machine Learning in Healthcare (16 papers) and Health Systems, Economic Evaluations, Quality of Life (7 papers). Suresh Balu collaborates with scholars based in United States, United Kingdom and Canada. Suresh Balu's co-authors include Mark Sendak, Michael Gao, Nathan Brajer, Marshall Nichols, William Ratliff, Cara O’Brien, Armando Bedoya, Kevin A. Schulman, Kristin Corey and Anthony Lin and has published in prestigious journals such as New England Journal of Medicine, JAMA and SHILAP Revista de lepidopterología.

In The Last Decade

Suresh Balu

48 papers receiving 1.1k citations

Peers

Suresh Balu

HIM

EPIDE

PHEOH

Suzanne Tamang United States

Jialin Liu China

Mark Sendak United States

Constanza L. Andaur Navarro Netherlands

Reed T. Sutton Canada

Erkin Ötleş United States

Jason Hom United States

Shmeylan Al Harbi Saudi Arabia

Nada Alsuhebany Saudi Arabia

Steven W J Nijman Netherlands

Suzanne Tamang United States

Suresh Balu

374 ×0.8

492 ×1.3

166 ×0.8

HIM

146 ×0.7

EPIDE

186 ×1.0

PHEOH

Citations per year, relative to Suresh Balu Suresh Balu (= 1×) peers Suzanne Tamang

Countries citing papers authored by Suresh Balu

Since Specialization

Citations

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

Fields of papers citing papers by Suresh Balu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suresh Balu

This figure shows the co-authorship network connecting the top 25 collaborators of Suresh Balu. A scholar is included among the top collaborators of Suresh Balu 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 Suresh Balu. Suresh Balu 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

Ma, Jessica, Clemontina A. Davenport, Maren K. Olsen, et al.. (2025). Impact of Prognostic Notifications on Inpatient Advance Care Planning: A Cluster Randomized Trial. Journal of Pain and Symptom Management. 70(6). 602–612.

Hasan, Alifia, David Vidal, Manesh R. Patel, et al.. (2025). Aligning AI principles and healthcare delivery organization best practices to navigate the shifting regulatory landscape. npj Digital Medicine. 8(1). 278–278.

Sendak, Mark, Meg Young, Alifia Hasan, et al.. (2025). Building models, building capacity: A review of participatory machine learning for HIV prevention. PLOS Global Public Health. 5(6). e0003862–e0003862. 1 indexed citations

Ma, Jessica, Alyssa Platt, Mark Sendak, et al.. (2024). Quality Improvement Study Using a Machine Learning Mortality Risk Prediction Model Notification System on Advance Care Planning in High-Risk Patients. PubMed. 3(3). 120907–120907. 1 indexed citations

Weissler, E. Hope, William Ratliff, Bradley J. Hintze, et al.. (2024). Development and Validation of a Natural Language Processing Model to Identify Low-Risk Pulmonary Embolism in Real Time to Facilitate Safe Outpatient Management. Annals of Emergency Medicine. 84(2). 118–127. 5 indexed citations

Senior, Rashaud, Timothy Tsai, William Ratliff, et al.. (2024). Evaluation of SNOMED CT Grouper Accuracy and Coverage in Organizing the Electronic Health Record Problem List by Clinical System: Observational Study. JMIR Medical Informatics. 12. e51274–e51274. 1 indexed citations

Boag, William, Alifia Hasan, Marshall Nichols, et al.. (2024). The algorithm journey map: a tangible approach to implementing AI solutions in healthcare. npj Digital Medicine. 7(1). 87–87. 6 indexed citations

Wolf, Steven, S. Yousuf Zafar, Suresh Balu, et al.. (2024). Machine Learning for Targeted Advance Care Planning in Cancer Patients: A Quality Improvement Study. Journal of Pain and Symptom Management. 68(6). 539–547.e3. 4 indexed citations

Hoodbhoy, Zahra, Henry David Jeffry Hogg, Alifia Hasan, et al.. (2024). Frameworks for procurement, integration, monitoring, and evaluation of artificial intelligence tools in clinical settings: A systematic review. PLOS Digital Health. 3(5). e0000514–e0000514. 12 indexed citations

10.

Sendak, Mark, Alifia Hasan, Mark A. Lifson, et al.. (2024). Empowering US healthcare delivery organizations: Cultivating a community of practice to harness AI and advance health equity. PLOS Digital Health. 3(6). e0000513–e0000513. 1 indexed citations

11.

Price, W. Nicholson, Mark Sendak, Suresh Balu, & Karandeep Singh. (2023). Enabling collaborative governance of medical AI. Nature Machine Intelligence. 5(8). 821–823. 14 indexed citations

12.

Boag, William, Alifia Hasan, Henry David Jeffry Hogg, et al.. (2023). Organizational Governance of Emerging Technologies: AI Adoption in Healthcare. 1396–1417. 19 indexed citations

13.

Hogg, Henry David Jeffry, Devdutta Sangvai, Manesh R. Patel, et al.. (2023). Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study. JMIR Formative Research. 7. e43963–e43963. 3 indexed citations

14.

Davis, Sharon E., Michael E. Matheny, Suresh Balu, & Mark Sendak. (2023). A framework for understanding label leakage in machine learning for health care. Journal of the American Medical Informatics Association. 31(1). 274–280. 7 indexed citations

15.

Bedoya, Armando, Nicoleta Economou-Zavlanos, Benjamin A. Goldstein, et al.. (2022). A framework for the oversight and local deployment of safe and high-quality prediction models. Journal of the American Medical Informatics Association. 29(9). 1631–1636. 58 indexed citations

16.

Henson, Jacqueline B., Hamed Zaribafzadeh, Mark Sendak, et al.. (2022). Social determinants of health data in solid organ transplantation: National data sources and future directions. American Journal of Transplantation. 22(10). 2293–2301. 15 indexed citations

17.

Kansal, Aman, Cynthia L. Green, Eric D. Peterson, et al.. (2021). Electronic Health Record Integration of Predictive Analytics to Select High-Risk Stable Patients With Non–ST-Segment–Elevation Myocardial Infarction for Intensive Care Unit Admission. Circulation Cardiovascular Quality and Outcomes. 14(4). e007602–e007602. 7 indexed citations

18.

Kansal, Aman, Michael Gao, Suresh Balu, et al.. (2021). Impact of diagnosis code grouping method on clinical prediction model performance: A multi-site retrospective observational study. International Journal of Medical Informatics. 151. 104466–104466. 4 indexed citations

19.

Sendak, Mark, Michael Gao, Nathan Brajer, & Suresh Balu. (2020). Presenting machine learning model information to clinical end users with model facts labels. npj Digital Medicine. 3(1). 41–41. 123 indexed citations

20.

Sendak, Mark, Michael Gao, Marshall Nichols, Anthony Lin, & Suresh Balu. (2019). Machine Learning in Health Care: A Critical Appraisal of Challenges and Opportunities. SHILAP Revista de lepidopterología. 7(1). 1–1. 51 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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