Akhil Vaid
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
Papers in
-
- Cardiovascular Function and Risk Factors 9
- ECG Monitoring and Analysis 9
-
- Machine Learning in Healthcare 9
- Topic Modeling 4
- Co-authors
- Girish N. Nadkarni (34 shared papers)Benjamin S. Glicksberg (18 shared papers)B. Keith Jenkins (1 shared paper)Rama Chellappa (1 shared paper)Alexander W. Charney (12 shared papers)Eyal Klang (4 shared papers)Edgar Argulian (6 shared papers)Dana Brin (1 shared paper)
- Journals
- Journal of the American College of Cardiology (5 papers)Clinical Journal of the American Society of Nephrology (3 papers)npj Digital Medicine (3 papers)Circulation (2 papers)The Lancet Digital Health (2 papers)
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Akhil Vaid
38 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Health Informatics 264
- Health Information Management 63
- Family Practice 30
- Cardiology and Cardiovascular Medicine 311
- Media Technology 108
Countries citing papers authored by Akhil Vaid
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
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.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1988 | 262 | |
| 2 | 2023 | 180 | |
| 3 | 2020 | 155 | |
| 4 | A foundation model for clinician-centered drug repurposing Hit paper breakdown → | 2024 | 72 |
| 5 | 2020 | 66 | |
| 6 | 2021 | 60 | |
| 7 | 2023 | 58 | |
| 8 | 2024 | 35 | |
| 9 | 2023 | 26 | |
| 10 | 2024 | 24 | |
| 11 | 2023 | 23 | |
| 12 | 2020 | 20 | |
| 13 | 2021 | 19 | |
| 14 | 2024 | 17 | |
| 15 | 2021 | 17 | |
| 16 | 2023 | 15 | |
| 17 | Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study Hit paper breakdown → | 2025 | 15 |
| 18 | 2024 | 13 | |
| 19 | 2020 | 12 | |
| 20 | 2024 | 12 |
About Akhil Vaid
Akhil Vaid is a scholar working on Cardiology and Cardiovascular Medicine, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Epidemiology and Pulmonary and Respiratory Medicine, having authored 48 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (9 papers), Machine Learning in Healthcare (9 papers), ECG Monitoring and Analysis (9 papers), Artificial Intelligence in Healthcare and Education (6 papers), Phonocardiography and Auscultation Techniques (5 papers), Sepsis Diagnosis and Treatment (5 papers), Cardiac Imaging and Diagnostics (4 papers) and Topic Modeling (4 papers). The work is most often cited by research in Health Informatics (264 citations), Health Information Management (63 citations), Family Practice (30 citations), Cardiology and Cardiovascular Medicine (311 citations) and Media Technology (108 citations). Akhil Vaid has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Girish N. Nadkarni, Benjamin S. Glicksberg, B. Keith Jenkins, Rama Chellappa, Alexander W. Charney, Eyal Klang, Edgar Argulian, Dana Brin, Ali Soroush and Vera Sorin. 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, Circulation and The Lancet Digital Health.
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.