Akhil Vaid

38 papers receiving 1.2k citations

Akhil Vaid's Hit Papers

Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study 2025 · 18 citations
180+1Years since publication255075

Peers

Akhil Vaid
Comparison fields: 5 of 123
  • Health Informatics 236
  • Cardiology and Cardiovascular Medicine 289
  • Health Information Management 58
  • Nephrology 84
  • Media Technology 106
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Citations per field
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Citations per year

Countries citing papers authored by Akhil Vaid

Since Specialization
Citations

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

Fields of papers citing papers by Akhil Vaid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Akhil Vaid, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Akhil Vaid Line = papers co-authored together Akhil Vaid links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988260
2 2023194
3 2020165
4
A foundation model for clinician-centered drug repurposing
Hit paper breakdown →
202492
5 202070
6 202366
7 202166
8 202437
9 202429
10 202327
11 202326
12 202421
13 202121
14 202020
15 202319
16 202118
17
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study
Hit paper breakdown →
202518
18 202414
19 202413
20 202012

About Akhil Vaid

Akhil Vaid is a scholar working on Cardiology and Cardiovascular Medicine, Health Informatics, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Health Information Management, having authored 42 papers that have together received 1.3k indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (9 papers), Cardiovascular Function and Risk Factors (6 papers), Artificial Intelligence in Healthcare and Education (6 papers), Machine Learning in Healthcare (5 papers), Cardiac Imaging and Diagnostics (4 papers), Artificial Intelligence in Healthcare (3 papers), Brain Tumor Detection and Classification (2 papers) and Sepsis Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (236 citations), Cardiology and Cardiovascular Medicine (289 citations), Health Information Management (58 citations), Nephrology (84 citations) and Media Technology (106 citations). Akhil Vaid has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Girish N. Nadkarni, Benjamin S. Glicksberg, B. Keith Jenkins, Rama Chellappa, Alexander W. Charney, Eyal Klang, Edgar Argulian, Jagat Narula, Vera Sorin and Ali Soroush. Their work appears in journals such as Journal of the American College of Cardiology, Clinical Journal of the American Society of Nephrology, npj Digital Medicine, Journal of the American Medical Informatics Association and Nature Communications.

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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