Roshanthi Weerasinghe

1.0k total citations
28 papers, 334 citations indexed

About

Roshanthi Weerasinghe is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Roshanthi Weerasinghe has authored 28 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Oncology, 8 papers in Pulmonary and Respiratory Medicine and 6 papers in Cancer Research. Recurrent topics in Roshanthi Weerasinghe's work include Global Cancer Incidence and Screening (5 papers), Lung Cancer Diagnosis and Treatment (4 papers) and Cancer Genomics and Diagnostics (4 papers). Roshanthi Weerasinghe is often cited by papers focused on Global Cancer Incidence and Screening (5 papers), Lung Cancer Diagnosis and Treatment (4 papers) and Cancer Genomics and Diagnostics (4 papers). Roshanthi Weerasinghe collaborates with scholars based in United States, France and Switzerland. Roshanthi Weerasinghe's co-authors include John T. Vetto, Birat Dhungel, Karen E. Deveney, Crystal J. Hessman, Paul H. Schipper, Christopher L. Corless, Heidi D Nelson, Peter E. Andersen, Neil D. Gross and Matthew W. Miller and has published in prestigious journals such as Circulation, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Roshanthi Weerasinghe

25 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Roshanthi Weerasinghe United States	9	166	76	62	55	55	28	334
Melissa Anne Mallory United States	10	180 1.1×	68 0.9×	90 1.5×	10 0.2×	12 0.2×	26	522
Max O. Meneveau United States	14	318 1.9×	54 0.7×	30 0.5×	8 0.1×	34 0.6×	35	647
Mihir Khunte United States	12	144 0.9×	59 0.8×	58 0.9×	93 1.7×	97 1.8×	63	570
Madelene Lewis United States	12	134 0.8×	96 1.3×	90 1.5×	104 1.9×	22 0.4×	25	513
Toms Vengaloor Thomas United States	9	183 1.1×	113 1.5×	29 0.5×	15 0.3×	31 0.6×	43	448
Adrienne B. Shannon United States	9	115 0.7×	53 0.7×	16 0.3×	16 0.3×	19 0.3×	39	213
Dana Smetherman United States	13	144 0.9×	92 1.2×	17 0.3×	7 0.1×	52 0.9×	27	649
Juliana Berk-Krauss United States	8	262 1.6×	18 0.2×	39 0.6×	34 0.6×	60 1.1×	17	463
Francis Spitz United States	11	264 1.6×	125 1.6×	34 0.5×	3 0.1×	70 1.3×	33	621
Krishnan R. Patel United States	9	42 0.3×	76 1.0×	57 0.9×	22 0.4×	43 0.8×	26	295

Countries citing papers authored by Roshanthi Weerasinghe

Since Specialization

Citations

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

Fields of papers citing papers by Roshanthi Weerasinghe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roshanthi Weerasinghe

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

Wong, Cliff, Zelalem Gero, Jaspreet Bagga, et al.. (2025). TRIALSCOPE — A Framework for Clinical Trial Simulation from Real-World Data. NEJM AI. 2(10). 2 indexed citations

Vita, Alessandro De, Douglas Hanes, Bela Bapat, et al.. (2024). Clinical impact for advanced non-small-cell lung cancer patients tested using comprehensive genomic profiling at a large USA health care system. SHILAP Revista de lepidopterología. 5. 100057–100057. 2 indexed citations

Bapat, Bela, Douglas Hanes, Shu‐Ching Chang, et al.. (2024). Widespread Adoption of Precision Anticancer Therapies After Implementation of Pathologist-Directed Comprehensive Genomic Profiling Across a Large US Health System. JCO Oncology Practice. 20(11). 1523–1532. 2 indexed citations

Weerasinghe, Roshanthi, Eleanor Wilson, Eduard Sidelnikov, et al.. (2024). Abstract 4136273: A Machine Learning Approach to Simplify Risk Stratification of Patients with Atherosclerotic Cardiovascular Disease. Circulation. 150(Suppl_1). 1 indexed citations

Li, Hsin‐Fang, et al.. (2024). Rates of Lipid Testing among Patients with Atherosclerotic Cardiovascular Disease within a Large Community-Based Health System. Journal of clinical lipidology. 18(4). e492–e492.

Simon, George R., Chiharu Sako, Ryan Beasley, et al.. (2023). AI-based radiomic biomarkers to predict PD-(L)1 immune checkpoint inhibitor response within PD-L1 high/low/negative expression categories in stage IV NSCLC.. Journal of Clinical Oncology. 41(16_suppl). 1517–1517. 1 indexed citations

Mu, Wei, Rajesh C. Rao, Robert Tinn, et al.. (2023). Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. Patterns. 4(4). 100726–100726. 15 indexed citations

Sako, Chiharu, Dwight H. Owen, Arya Amini, et al.. (2023). Multi-center real-world data curation and assessment of tumor growth rate and overall survival in advanced NSCLC treated with PD-(L)1 immune checkpoint inhibitor therapy.. Journal of Clinical Oncology. 41(16_suppl). 9124–9124. 1 indexed citations

Saria, Suchi, Brian Piening, Brendan D. Curti, et al.. (2022). A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy. Cancer Informatics. 21. 2663762641–2663762641. 3 indexed citations

10.

Epstein, Robert S., et al.. (2021). Real-world burden of chemotherapy-induced myelosuppression in patients with small cell lung cancer: a retrospective analysis of electronic medical data from community cancer care providers. Journal of Medical Economics. 25(1). 108–118. 19 indexed citations

11.

Drescher, Charles W., et al.. (2021). Cancer case trends following the onset of the COVID‐19 pandemic: A community‐based observational study with extended follow‐up. Cancer. 128(7). 1475–1482. 19 indexed citations

12.

Uppal, Abhineet, Brooke Vuong, Ahmed Dehal, et al.. (2018). Can high-volume teams of anesthesiologists and surgeons decrease perioperative costs for pancreatic surgery?. HPB. 21(5). 589–595. 5 indexed citations

13.

Wilshire, Candice L., Elke Rauch, John R. Handy, et al.. (2018). P2.11-21 Factors Predicting Attrition in Community-Based Healthcare Network Lung Cancer Screening Programs. Journal of Thoracic Oncology. 13(10). S786–S787. 1 indexed citations

14.

Vuong, Brooke, Ahmed Dehal, Abhineet Uppal, et al.. (2018). What Are the Most Significant Cost and Value Drivers for Pancreatic Resection in an Integrated Healthcare System?. Journal of the American College of Surgeons. 227(1). 45–53. 13 indexed citations

15.

Tseng, Jennifer, Birat Dhungel, Jane K. Mills, et al.. (2014). Merkel cell carcinoma: what makes a difference?. The American Journal of Surgery. 209(2). 342–346. 8 indexed citations

16.

Nelson, Heidi D, Roshanthi Weerasinghe, Maritza Martel, et al.. (2014). Development of an electronic breast pathology database in a community health system. Journal of Pathology Informatics. 5(1). 26–26. 8 indexed citations

17.

Nelson, Heidi D & Roshanthi Weerasinghe. (2013). Actualizing Personalized Healthcare for Women through Connected Data Systems: Breast Cancer Screening and Diagnosis. Global Advances in Health and Medicine. 2(5). 30–36. 5 indexed citations

18.

Hessman, Crystal J., et al.. (2011). Comparison of pulmonary nodule detection rates between preoperative CT imaging and intraoperative lung palpation. The American Journal of Surgery. 201(5). 619–622. 46 indexed citations

19.

Dhungel, Birat, et al.. (2011). Trends in Research Time, Fellowship Training, and Practice Patterns Among General Surgery Graduates. Journal of surgical education. 68(4). 309–312. 81 indexed citations

20.

Weerasinghe, Roshanthi, et al.. (2010). Sentinel lymph node staging of cutaneous melanoma: predictors and outcomes. The American Journal of Surgery. 199(5). 663–668. 36 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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