Brihat Sharma

528 total citations
21 papers, 313 citations indexed

About

Brihat Sharma is a scholar working on Public Health, Environmental and Occupational Health, Epidemiology and Artificial Intelligence. According to data from OpenAlex, Brihat Sharma has authored 21 papers receiving a total of 313 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Public Health, Environmental and Occupational Health, 8 papers in Epidemiology and 7 papers in Artificial Intelligence. Recurrent topics in Brihat Sharma's work include Opioid Use Disorder Treatment (10 papers), Substance Abuse Treatment and Outcomes (7 papers) and Machine Learning in Healthcare (6 papers). Brihat Sharma is often cited by papers focused on Opioid Use Disorder Treatment (10 papers), Substance Abuse Treatment and Outcomes (7 papers) and Machine Learning in Healthcare (6 papers). Brihat Sharma collaborates with scholars based in United States and Spain. Brihat Sharma's co-authors include Majid Afshar, Niranjan S. Karnik, Dmitriy Dligach, Hale M. Thompson, Cara Joyce, Matthew M. Churpek, Randy A. Boley, Elizabeth Salisbury‐Afshar, Walter Faig and Nicole A. VanKim and has published in prestigious journals such as PLoS ONE, International Journal of Environmental Research and Public Health and Addiction.

In The Last Decade

Brihat Sharma

21 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Brihat Sharma United States	12	120	103	83	55	36	21	313
Sina Rashidian United States	10	94 0.8×	86 0.8×	77 0.9×	28 0.5×	21 0.6×	21	283
Mary Saltz United States	11	103 0.9×	111 1.1×	83 1.0×	24 0.4×	22 0.6×	18	326
David Cronkite United States	11	192 1.6×	92 0.9×	103 1.2×	20 0.4×	22 0.6×	25	405
Anthony Lin United States	7	67 0.6×	99 1.0×	93 1.1×	82 1.5×	43 1.2×	16	433
James L. Huang United States	6	163 1.4×	50 0.5×	111 1.3×	14 0.3×	25 0.7×	13	288
Sena Chae United States	10	57 0.5×	53 0.5×	39 0.5×	28 0.5×	47 1.3×	30	269
Wenyu Song United States	10	44 0.4×	28 0.3×	43 0.5×	28 0.5×	20 0.6×	28	264
Wen‐Hui Fang Taiwan	13	102 0.8×	50 0.5×	57 0.7×	25 0.5×	15 0.4×	32	475
Jackson Steinkamp United States	12	73 0.6×	90 0.9×	39 0.5×	60 1.1×	38 1.1×	23	339
Morgan Simons United States	6	24 0.2×	155 1.5×	93 1.1×	98 1.8×	31 0.9×	6	353

Countries citing papers authored by Brihat Sharma

Since Specialization

Citations

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

Fields of papers citing papers by Brihat Sharma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brihat Sharma

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

Sharma, Brihat, et al.. (2024). Transatlantic transferability and replicability of machine-learning algorithms to predict mental health crises. npj Digital Medicine. 7(1). 227–227. 2 indexed citations

Afshar, Majid, Marlon P. Mundt, Randall Brown, et al.. (2023). Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults. JMIR Medical Informatics. 11. e44977–e44977. 14 indexed citations

Gao, Yanjun, Dmitriy Dligach, Timothy A. Miller, et al.. (2023). DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing. Journal of Biomedical Informatics. 138. 104286–104286. 12 indexed citations

Sharma, Brihat, Yanjun Gao, Timothy A. Miller, et al.. (2023). Multi-Task Training with In-Domain Language Models for Diagnostic Reasoning. PubMed. 2023(ClinicalNLP). 78–85. 8 indexed citations

Chhabra, Neeraj, et al.. (2023). Performance of International Classification of Disease‐10 codes in detecting emergency department patients with opioid misuse. Addiction. 119(4). 766–771. 4 indexed citations

Thompson, Hale M., Brihat Sharma, Dale L. Smith, et al.. (2022). Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study. JMIR Public Health and Surveillance. 8(12). e38158–e38158. 2 indexed citations

Chhabra, Neeraj, et al.. (2022). The Identification of Subphenotypes and Associations with Health Outcomes in Patients with Opioid-Related Emergency Department Encounters Using Latent Class Analysis. International Journal of Environmental Research and Public Health. 19(14). 8882–8882. 2 indexed citations

Joyce, Cara, Talar Markossian, Hale M. Thompson, et al.. (2022). The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design. JMIR Research Protocols. 11(12). e42971–e42971. 2 indexed citations

Afshar, Majid, Brihat Sharma, Dmitriy Dligach, et al.. (2022). Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study. The Lancet Digital Health. 4(6). e426–e435. 25 indexed citations

10.

Sharma, Brihat, Hale M. Thompson, Randy A. Boley, et al.. (2021). External validation of a machine learning classifier to identify unhealthy alcohol use in hospitalized patients. Addiction. 117(4). 925–933. 7 indexed citations

11.

Afshar, Majid, Brihat Sharma, Hale M. Thompson, et al.. (2021). External validation of an opioid misuse machine learning classifier in hospitalized adult patients. Addiction Science & Clinical Practice. 16(1). 19–19. 21 indexed citations

12.

Joyce, Cara, et al.. (2021). The Addition of United States Census-Tract Data Does Not Improve the Prediction of Substance Misuse.. PubMed. 2021. 1149–1158. 2 indexed citations

13.

Sharma, Brihat, Dale L. Smith, Randy A. Boley, et al.. (2021). Investigating Unhealthy Alcohol Use As an Independent Risk Factor for Increased COVID-19 Disease Severity: Observational Cross-sectional Study. JMIR Public Health and Surveillance. 7(11). e33022–e33022. 17 indexed citations

14.

Afshar, Majid, Brihat Sharma, Dmitriy Dligach, et al.. (2021). Substance Misuse Algorithm for Referral to Treatment Using Artificial Intelligence (SMART-AI): Multi-Modal Validation with Interpretation and Bias Assessment. SSRN Electronic Journal. 1 indexed citations

15.

Thompson, Hale M., Walter Faig, Nicole A. VanKim, et al.. (2020). Differences in length of stay and discharge destination among patients with substance use disorders: The effect of Substance Use Intervention Team (SUIT) consultation service. PLoS ONE. 15(10). e0239761–e0239761. 28 indexed citations

16.

Sharma, Brihat, Dmitriy Dligach, Elizabeth Salisbury‐Afshar, et al.. (2020). Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients. BMC Medical Informatics and Decision Making. 20(1). 79–79. 24 indexed citations

17.

Afshar, Majid, Cara Joyce, Dmitriy Dligach, et al.. (2019). Subtypes in patients with opioid misuse: A prognostic enrichment strategy using electronic health record data in hospitalized patients. PLoS ONE. 14(7). e0219717–e0219717. 36 indexed citations

18.

Sharma, Brihat, et al.. (2019). Validation of an alcohol misuse classifier in hospitalized patients. Alcohol. 84. 49–55. 18 indexed citations

19.

Afshar, Majid, et al.. (2019). Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies. Journal of the American Medical Informatics Association. 26(11). 1364–1369. 22 indexed citations

20.

Sharma, Brihat, et al.. (2018). Merkle-Tree Based Approach for Ensuring Integrity of Electronic Medical Records. 983–987. 13 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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