Lina Sulieman

792 total citations
18 papers, 255 citations indexed

About

Lina Sulieman is a scholar working on General Health Professions, Health Information Management and Artificial Intelligence. According to data from OpenAlex, Lina Sulieman has authored 18 papers receiving a total of 255 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in General Health Professions, 8 papers in Health Information Management and 4 papers in Artificial Intelligence. Recurrent topics in Lina Sulieman's work include Electronic Health Records Systems (7 papers), Health Literacy and Information Accessibility (5 papers) and Ethics in Clinical Research (3 papers). Lina Sulieman is often cited by papers focused on Electronic Health Records Systems (7 papers), Health Literacy and Information Accessibility (5 papers) and Ethics in Clinical Research (3 papers). Lina Sulieman collaborates with scholars based in United States and Canada. Lina Sulieman's co-authors include Bradley Malin, Zhijun Yin, Bryan D. Steitz, Adam Wright, Gretchen Purcell Jackson, Robert M. Cronin, Daniel Fabbri, Andrea H. Ramirez, Paul A. Harris and Brandy Mapes and has published in prestigious journals such as PLoS ONE, Journal of the American Medical Informatics Association and JAMA Network Open.

In The Last Decade

Lina Sulieman

18 papers receiving 252 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lina Sulieman United States 8 76 67 62 50 22 18 255
Noah Crampton Canada 8 115 1.5× 71 1.1× 62 1.0× 25 0.5× 33 1.5× 18 280
Roy T. Sabo United States 9 115 1.5× 48 0.7× 63 1.0× 20 0.4× 23 1.0× 30 343
Mohy Uddin Saudi Arabia 10 78 1.0× 40 0.6× 76 1.2× 70 1.4× 7 0.3× 24 437
Jessica Baldwin United States 8 180 2.4× 89 1.3× 73 1.2× 19 0.4× 29 1.3× 17 364
Kevin Lybarger United States 9 64 0.8× 42 0.6× 21 0.3× 101 2.0× 13 0.6× 31 236
Randa Perkins United States 7 75 1.0× 91 1.4× 59 1.0× 17 0.3× 29 1.3× 12 289
Jackson Steinkamp United States 12 55 0.7× 38 0.6× 73 1.2× 90 1.8× 10 0.5× 23 339
Bryan D. Steitz United States 10 156 2.1× 134 2.0× 83 1.3× 44 0.9× 59 2.7× 33 355
Mst. Rina Parvin Bangladesh 10 42 0.6× 52 0.8× 76 1.2× 93 1.9× 17 0.8× 23 405
Hiral Soni United States 11 96 1.3× 33 0.5× 98 1.6× 17 0.3× 17 0.8× 37 277

Countries citing papers authored by Lina Sulieman

Since Specialization
Citations

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

Fields of papers citing papers by Lina Sulieman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lina Sulieman

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

All Works

18 of 18 papers shown
1.
Berman, Lewis E., et al.. (2024). Application of a Data Quality Framework to Ductal Carcinoma In Situ Using Electronic Health Record Data From the All of Us Research Program. JCO Clinical Cancer Informatics. 8(8). e2400052–e2400052. 1 indexed citations
2.
Sulieman, Lina, et al.. (2024). Illuminating the landscape of high-level clinical trial opportunities in the All of Us Research Program. Journal of the American Medical Informatics Association. 31(12). 2890–2898. 2 indexed citations
3.
Schlueter, David J., Lina Sulieman, Huan Mo, et al.. (2023). Systematic replication of smoking disease associations using survey responses and EHR data in the All of Us Research Program. Journal of the American Medical Informatics Association. 31(1). 139–153. 6 indexed citations
4.
Cronin, Robert M., Xiaoke Feng, Lina Sulieman, et al.. (2023). Importance of missingness in baseline variables: A case study of the All of Us Research Program. PLoS ONE. 18(5). e0285848–e0285848. 3 indexed citations
5.
Sulieman, Lina, et al.. (2023). A Case Report on the Effectiveness of Virtual Monitoring of Postdischarge COVID-19 Positive Patients in a Rural Hospital Setting: A Retrospective Review. Telemedicine Journal and e-Health. 30(1). 291–297. 1 indexed citations
6.
7.
Benda, Natalie C., Mohit Sharma, Lisa C. Diamond, et al.. (2022). Identifying Nonpatient Authors of Patient Portal Secure Messages in Oncology: A Proof-of-Concept Demonstration of Natural Language Processing Methods. JCO Clinical Cancer Informatics. 6(6). e2200071–e2200071. 5 indexed citations
8.
Lau, Chun Yee, et al.. (2022). EHR Data Quality Assessment Tools and Issue Reporting Workflows for the 'All of Us' Research Program Clinical Data Research Network.. PubMed. 2022. 186–195. 10 indexed citations
9.
Sulieman, Lina, Robert M. Cronin, Robert J. Carroll, et al.. (2022). Comparing medical history data derived from electronic health records and survey answers in the All of Us Research Program. Journal of the American Medical Informatics Association. 29(7). 1131–1141. 21 indexed citations
10.
Karnes, Jason H., Amit Arora, Heidi E. Steiner, et al.. (2021). Racial, ethnic, and gender differences in obesity and body fat distribution: An All of Us Research Program demonstration project. PLoS ONE. 16(8). e0255583–e0255583. 37 indexed citations
11.
Steitz, Bryan D., et al.. (2021). Association of Immediate Release of Test Results to Patients With Implications for Clinical Workflow. JAMA Network Open. 4(10). e2129553–e2129553. 43 indexed citations
12.
Steitz, Bryan D., et al.. (2021). Classification and analysis of asynchronous communication content between care team members involved in breast cancer treatment. JAMIA Open. 4(3). ooab049–ooab049. 7 indexed citations
13.
Sulieman, Lina, Jamie R. Robinson, & Gretchen Purcell Jackson. (2020). Automating the Classification of Complexity of Medical Decision-Making in Patient-Provider Messaging in a Patient Portal. Journal of Surgical Research. 255. 224–232. 10 indexed citations
14.
Sulieman, Lina, Bryan D. Steitz, & S. Trent Rosenbloom. (2020). Analysis of Employee Patient Portal Use and Electronic Health Record Access at an Academic Medical Center. Applied Clinical Informatics. 11(3). 433–441. 9 indexed citations
15.
Sulieman, Lina, Zhijun Yin, & Bradley Malin. (2019). Why Patient Portal Messages Indicate Risk of Readmission for Patients with Ischemic Heart Disease.. PubMed. 2019. 828–837. 7 indexed citations
16.
Yin, Zhijun, Lina Sulieman, & Bradley Malin. (2019). A systematic literature review of machine learning in online personal health data. Journal of the American Medical Informatics Association. 26(6). 561–576. 49 indexed citations
17.
Sulieman, Lina, et al.. (2017). Classifying patient portal messages using Convolutional Neural Networks. Journal of Biomedical Informatics. 74. 59–70. 41 indexed citations
18.
Sulieman, Lina, Daniel Fabbri, Fei Wang, Jianying Hu, & Bradley Malin. (2016). Predicting Negative Events: Using Post-discharge Data to Detect High-Risk Patients.. PubMed. 2016. 1169–1178. 2 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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