Dev Dash

1.1k total citations · 1 hit paper
9 papers, 209 citations indexed

About

Dev Dash is a scholar working on Artificial Intelligence, Health Informatics and Surgery. According to data from OpenAlex, Dev Dash has authored 9 papers receiving a total of 209 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Health Informatics and 2 papers in Surgery. Recurrent topics in Dev Dash's work include Machine Learning in Healthcare (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Artificial Intelligence in Healthcare (2 papers). Dev Dash is often cited by papers focused on Machine Learning in Healthcare (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Artificial Intelligence in Healthcare (2 papers). Dev Dash collaborates with scholars based in United States and Thailand. Dev Dash's co-authors include Alison Callahan, Nigam H. Shah, Michael A. Pfeffer, Nirav R. Shah, Oluwasanmi Koyejo, Lisa Soleymani Lehmann, Mehr Kashyap, Akshay Swaminathan, Jason Fries and Suhana Bedi and has published in prestigious journals such as JAMA, Annals of Emergency Medicine and JAMA Network Open.

In The Last Decade

Dev Dash

9 papers receiving 204 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.

Testing and Evaluation of Health Care Applications of Large Language Models

2024 137 citations Suhana Bedi, Dev Dash et al. JAMA profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dev Dash United States	6	112	73	50	23	16	9	209
Joshua Au Yeung United Kingdom	7	118 1.1×	92 1.3×	45 0.9×	27 1.2×	19 1.2×	11	224
Brenda Y. Miao United States	8	125 1.1×	104 1.4×	72 1.4×	16 0.7×	23 1.4×	14	287
Sophia M. Pressman United States	9	146 1.3×	64 0.9×	51 1.0×	26 1.1×	21 1.3×	18	229
Shawheen J. Rezaei United States	6	81 0.7×	60 0.8×	39 0.8×	14 0.6×	18 1.1×	26	239
Cesar A. Gomez-Cabello United States	10	162 1.4×	72 1.0×	54 1.1×	28 1.2×	27 1.7×	34	265
Asad Aali United States	3	109 1.0×	131 1.8×	55 1.1×	23 1.0×	15 0.9×	6	268
Cara Van Uden United States	2	116 1.0×	139 1.9×	56 1.1×	22 1.0×	15 0.9×	2	263
Joséphine A. Cool United States	6	115 1.0×	71 1.0×	35 0.7×	12 0.5×	17 1.1×	15	302
Shan Chen United States	5	88 0.8×	105 1.4×	39 0.8×	33 1.4×	34 2.1×	9	231
Mohammad Delsoz United States	7	117 1.0×	48 0.7×	128 2.6×	10 0.4×	9 0.6×	15	214

Countries citing papers authored by Dev Dash

Since Specialization

Citations

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

Fields of papers citing papers by Dev Dash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dev Dash

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Dai, Wei, Ehsan Adeli, Dev Dash, et al.. (2025). Developing ICU Clinical Behavioral Atlas Using Ambient Intelligence and Computer Vision. NEJM AI. 2(2). 2 indexed citations

2.

Bedi, Suhana, Dev Dash, Oluwasanmi Koyejo, et al.. (2024). A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs). medRxiv. 16 indexed citations

3.

Li, Wenjun, et al.. (2024). 134 Emergency Department Admitting Service Triage Using Retrieval-Augmented Language Models. Annals of Emergency Medicine. 84(4). S63–S63. 1 indexed citations

4.

Warman, Anmol, Andrew J. Degnan, Johan G. Blickman, et al.. (2024). Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels. Emergency Medicine Journal. 41(5). 298–303. 2 indexed citations

5.

Bedi, Suhana, Dev Dash, Oluwasanmi Koyejo, et al.. (2024). Testing and Evaluation of Health Care Applications of Large Language Models. JAMA. 333(4). 319–319. 137 indexed citations breakdown →

6.

He, Bryan, et al.. (2023). AI-ENABLED ASSESSMENT OF CARDIAC FUNCTION AND VIDEO QUALITY IN EMERGENCY DEPARTMENT POINT-OF-CARE ECHOCARDIOGRAMS. Journal of Emergency Medicine. 66(2). 184–191. 6 indexed citations

7.

Warman, Anmol, Andrew J. Degnan, Johan G. Blickman, et al.. (2022). Deep Learning System Boosts Radiologist Detection of Intracranial Hemorrhage. Cureus. 14(10). e30264–e30264. 10 indexed citations

8.

Dash, Dev, Birju Patel, Alison Callahan, et al.. (2022). Building a Learning Health System: Creating an Analytical Workflow for Evidence Generation to Inform Institutional Clinical Care Guidelines. Applied Clinical Informatics. 13(1). 315–321. 6 indexed citations

9.

Callahan, Alison, Birju Patel, Keith Morse, et al.. (2022). Assessment of Adherence to Reporting Guidelines by Commonly Used Clinical Prediction Models From a Single Vendor. JAMA Network Open. 5(8). e2227779–e2227779. 29 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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