Mark Sendak

3.7k total citations · 1 hit paper
54 papers, 1.6k citations indexed

About

Mark Sendak is a scholar working on Health Informatics, Artificial Intelligence and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Mark Sendak has authored 54 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Health Informatics, 20 papers in Artificial Intelligence and 17 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Mark Sendak's work include Artificial Intelligence in Healthcare and Education (21 papers), Machine Learning in Healthcare (19 papers) and Ethics in Clinical Research (8 papers). Mark Sendak is often cited by papers focused on Artificial Intelligence in Healthcare and Education (21 papers), Machine Learning in Healthcare (19 papers) and Ethics in Clinical Research (8 papers). Mark Sendak collaborates with scholars based in United States, United Kingdom and Canada. Mark Sendak's co-authors include Suresh Balu, Michael Gao, Katherine Heller, Nathan Brajer, Marshall Nichols, Sonoo Thadaney-Israni, Mohammed Saeed, Kenneth Jung, Anna Goldenberg and David C. Kale and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and Clinical Infectious Diseases.

In The Last Decade

Mark Sendak

47 papers receiving 1.6k 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.

Do no harm: a roadmap for responsible machine learning for health care

2019 506 citations Jenna Wiens, Mark Sendak et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Sendak United States	18	728	582	294	283	280	54	1.6k
Hisham A. Badreldin Saudi Arabia	12	689 0.9×	371 0.6×	183 0.6×	289 1.0×	110 0.4×	51	1.9k
Trishan Panch United States	13	576 0.8×	415 0.7×	186 0.6×	316 1.1×	137 0.5×	22	1.6k
Suresh Balu United States	16	446 0.6×	374 0.6×	206 0.7×	158 0.6×	204 0.7×	54	1.1k
Matthieu Komorowski United Kingdom	20	617 0.8×	694 1.2×	156 0.5×	431 1.5×	470 1.7×	63	2.3k
Majed S. Al Yami Saudi Arabia	12	687 0.9×	367 0.6×	176 0.6×	286 1.0×	112 0.4×	53	1.8k
Danton Char United States	13	771 1.1×	382 0.7×	176 0.6×	368 1.3×	92 0.3×	45	1.6k
Abdulrahman Alshaya Saudi Arabia	9	686 0.9×	368 0.6×	178 0.6×	285 1.0×	87 0.3×	31	1.6k
Khalid Bin Saleh Saudi Arabia	9	685 0.9×	369 0.6×	176 0.6×	284 1.0×	98 0.3×	29	1.6k
Jialin Liu China	17	531 0.7×	385 0.7×	145 0.5×	273 1.0×	149 0.5×	64	1.4k
Shmeylan Al Harbi Saudi Arabia	11	617 0.8×	296 0.5×	176 0.6×	297 1.0×	110 0.4×	25	1.5k

Countries citing papers authored by Mark Sendak

Since Specialization

Citations

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

Fields of papers citing papers by Mark Sendak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Sendak

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

Urteaga, Iñigo, George Hripcsak, Pierre Elias, et al.. (2025). AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. Journal of the American Medical Informatics Association. 32(3). 589–594. 4 indexed citations

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

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.

Smith, Claire, et al.. (2024). From pre-test and post-test probabilities to medical decision making. BMC Medical Informatics and Decision Making. 24(1). 210–210.

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.

Movva, Naimisha, Mina Suh, Heidi Reichert, et al.. (2022). Respiratory Syncytial Virus During the COVID-19 Pandemic Compared to Historic Levels: A Retrospective Cohort Study of a Health System. The Journal of Infectious Diseases. 226(Supplement_2). S175–S183. 23 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, 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

20.

Futoma, Joseph, Mark Sendak, C. Blake Cameron, & Katherine Heller. (2016). Scalable joint modeling of longitudinal and point process data for disease trajectory prediction and improving Management of Chronic Kidney Disease. Uncertainty in Artificial Intelligence. 222–231. 6 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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