Aditya Biswas

864 total citations
18 papers, 418 citations indexed

About

Aditya Biswas is a scholar working on Nephrology, Cardiology and Cardiovascular Medicine and Epidemiology. According to data from OpenAlex, Aditya Biswas has authored 18 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Nephrology, 7 papers in Cardiology and Cardiovascular Medicine and 4 papers in Epidemiology. Recurrent topics in Aditya Biswas's work include Acute Kidney Injury Research (8 papers), Chronic Kidney Disease and Diabetes (4 papers) and Blood Pressure and Hypertension Studies (3 papers). Aditya Biswas is often cited by papers focused on Acute Kidney Injury Research (8 papers), Chronic Kidney Disease and Diabetes (4 papers) and Blood Pressure and Hypertension Studies (3 papers). Aditya Biswas collaborates with scholars based in United States, India and Canada. Aditya Biswas's co-authors include F. Perry Wilson, Yu Yamamoto, Michael Simonov, Lama Ghazi, Melissa Martin, Jason H. Greenberg, Ugochukwu Ugwuowo, Sherry G. Mansour, Dennis G. Moledina and Jeffrey M. Testani and has published in prestigious journals such as PLoS ONE, Genome Research and Journal of the American Society of Nephrology.

In The Last Decade

Aditya Biswas

17 papers receiving 411 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aditya Biswas United States	11	181	110	71	69	66	18	418
Tukaram Jamale India	9	228 1.3×	99 0.9×	23 0.3×	61 0.9×	96 1.5×	32	416
Paul Gabarre France	6	105 0.6×	302 2.7×	25 0.4×	117 1.7×	85 1.3×	26	484
Andrew J. Vincz United States	10	171 0.9×	45 0.4×	28 0.4×	36 0.5×	53 0.8×	12	315
Priya Simoes United States	13	129 0.7×	29 0.3×	91 1.3×	149 2.2×	88 1.3×	30	485
Thomas Dienemann Germany	11	89 0.5×	61 0.6×	70 1.0×	81 1.2×	33 0.5×	24	411
Sharidan K. Parr United States	14	457 2.5×	39 0.4×	56 0.8×	75 1.1×	72 1.1×	17	637
Bertrand Guidet France	7	63 0.3×	61 0.6×	72 1.0×	29 0.4×	127 1.9×	17	308
Maria Cronhjort Sweden	9	81 0.4×	68 0.6×	55 0.8×	157 2.3×	170 2.6×	36	395
Amy M. Perkins United States	12	121 0.7×	28 0.3×	43 0.6×	53 0.8×	73 1.1×	28	367
Thananda Trakarnvanich Thailand	8	235 1.3×	37 0.3×	37 0.5×	56 0.8×	48 0.7×	35	356

Countries citing papers authored by Aditya Biswas

Since Specialization

Citations

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

Fields of papers citing papers by Aditya Biswas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aditya Biswas

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

All Works

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18 of 18 papers shown

Ghazi, Lama, Xinyuan Chen, Michael O. Harhay, et al.. (2024). Treatment Effect Heterogeneity in Acute Kidney Injury Incidence Following Intravenous Antihypertensive Administration for Severe Blood Pressure Elevation During Hospitalization. American Journal of Kidney Diseases. 85(4). 442–453.

Ghazi, Lama, Fan Li, Xinyuan Chen, et al.. (2022). Severe inpatient hypertension prevalence and blood pressure response to antihypertensive treatment. Journal of Clinical Hypertension. 24(3). 339–349. 10 indexed citations

Ghazi, Lama, Fan Li, Xinyuan Chen, et al.. (2022). Blood pressure response to commonly administered antihypertensives for severe inpatient hypertension. PLoS ONE. 17(4). e0265497–e0265497. 5 indexed citations

Ahmad, Tariq, Nihar R. Desai, Yu Yamamoto, et al.. (2022). Alerting Clinicians to 1-Year Mortality Risk in Patients Hospitalized With Heart Failure. JAMA Cardiology. 7(9). 905–905. 32 indexed citations

Biswas, Aditya, Chad Sanada, Ujjwal Maulik, et al.. (2021). Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data. Genome Research. 31(4). 689–697. 10 indexed citations

Moledina, Dennis G., Michael Simonov, Yu Yamamoto, et al.. (2021). The Association of COVID-19 With Acute Kidney Injury Independent of Severity of Illness: A Multicenter Cohort Study. American Journal of Kidney Diseases. 77(4). 490–499.e1. 59 indexed citations

Ghazi, Lama, Michael Simonov, Sherry G. Mansour, et al.. (2021). Predicting patients with false negative SARS-CoV-2 testing at hospital admission: A retrospective multi-center study. PLoS ONE. 16(5). e0251376–e0251376. 2 indexed citations

Biswas, Aditya, et al.. (2021). Introduction to Supervised Machine Learning. Kidney360. 2(5). 878–880. 17 indexed citations

Ahmad, Tariq, Yu Yamamoto, Aditya Biswas, et al.. (2021). REVeAL-HF. JACC Heart Failure. 9(6). 409–419. 15 indexed citations

10.

Nugent, James T., Abinet M. Aklilu, Yu Yamamoto, et al.. (2021). Assessment of Acute Kidney Injury and Longitudinal Kidney Function After Hospital Discharge Among Patients With and Without COVID-19. JAMA Network Open. 4(3). e211095–e211095. 104 indexed citations

11.

Ugwuowo, Ugochukwu, Yu Yamamoto, Tanima Arora, et al.. (2020). Real-Time Prediction of Acute Kidney Injury in Hospitalized Adults: Implementation and Proof of Concept. American Journal of Kidney Diseases. 76(6). 806–814.e1. 14 indexed citations

12.

Yamamoto, Yu, Aditya Biswas, Tanima Arora, et al.. (2020). A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children. Journal of the American Society of Nephrology. 31(6). 1348–1357. 33 indexed citations

13.

Simonov, Michael, Ugochukwu Ugwuowo, Yu Yamamoto, et al.. (2019). A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: A descriptive modeling study. PLoS Medicine. 16(7). e1002861–e1002861. 48 indexed citations

14.

Martin, Melissa, Yu Yamamoto, Aditya Biswas, et al.. (2019). Electronic Alerts for Acute Kidney Injury Amelioration (ELAIA-1): a completely electronic, multicentre, randomised controlled trial: design and rationale. BMJ Open. 9(5). e025117–e025117. 14 indexed citations

15.

Biswas, Aditya, Sharmistha Bhattacherjee, & Abhijit Mukherjee. (2018). Quality of Life among adolescents studying in Bengali and English medium schools of Siliguri subdivision, Darjeeling district, West Bengal. 6(1). 30–36. 1 indexed citations

16.

Biswas, Aditya, Chirag R. Parikh, Harold I. Feldman, et al.. (2018). Identification of Patients Expected to Benefit from Electronic Alerts for Acute Kidney Injury. Clinical Journal of the American Society of Nephrology. 13(6). 842–849. 23 indexed citations

17.

Sun, Qisi, Jeffrey M. Testani, Chirag R. Parikh, et al.. (2017). Approaches to Predicting Outcomes in Patients with Acute Kidney Injury. PLoS ONE. 12(1). e0169305–e0169305. 27 indexed citations

18.

Sinha, Debanjali, et al.. (1996). Studies on prosthetic valve function--a transesophageal echocardiographic assessment.. PubMed. 44(8). 525–8. 4 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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