Arash Kia
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Machine Learning in Healthcare 4
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- Nutrition and Health in Aging 3
- Co-authors
- Prem Timsina (18 shared papers)Robert Freeman (17 shared papers)Madhu Mazumdar (10 shared papers)Matthew A. Levin (15 shared papers)David L. Reich (11 shared papers)Himanshu Joshi (5 shared papers)Roopa Kohli‐Seth (5 shared papers)Pranai Tandon (5 shared papers)
- Journals
- Journal of Clinical Medicine (4 papers)Critical Care Medicine (2 papers)JAMA Network Open (2 papers)Journal of Human Nutrition and Dietetics (1 paper)BMJ Supportive & Palliative Care (1 paper)
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Arash Kia
22 papers receiving 363 citations
Peers
Comparison fields: 5 of 67
- Health Informatics 43
- Health Information Management 31
- Radiology, Nuclear Medicine and Imaging 91
- Emergency Medicine 31
- Modeling and Simulation 13
Countries citing papers authored by Arash Kia
This map shows the geographic impact of Arash Kia'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 Arash Kia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arash Kia more than expected).
Fields of papers citing papers by Arash Kia
This network shows the impact of papers produced by Arash Kia. 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 Arash Kia. The network helps show where Arash Kia may publish in the future.
Co-authors
The 25 scholars most cited alongside Arash Kia, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 121 | |
| 2 | 2020 | 39 | |
| 3 | 2020 | 39 | |
| 4 | 2021 | 31 | |
| 5 | 2010 | 28 | |
| 6 | 2020 | 27 | |
| 7 | 2021 | 18 | |
| 8 | 2022 | 9 | |
| 9 | 2024 | 8 | |
| 10 | 2024 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 6 | |
| 13 | 2023 | 5 | |
| 14 | 2024 | 5 | |
| 15 | 2025 | 5 | |
| 16 | 2024 | 4 | |
| 17 | 2020 | 4 | |
| 18 | 2025 | 3 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 1 |
About Arash Kia
Arash Kia is a scholar working on Artificial Intelligence, Physiology, Emergency Medicine, Critical Care and Intensive Care Medicine and Pulmonary and Respiratory Medicine, having authored 26 papers that have together received 369 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Emergency and Acute Care Studies (3 papers), Nutrition and Health in Aging (3 papers), Respiratory Support and Mechanisms (2 papers), Intensive Care Unit Cognitive Disorders (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Frailty in Older Adults (2 papers) and Sepsis Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (43 citations), Health Information Management (31 citations), Radiology, Nuclear Medicine and Imaging (91 citations), Emergency Medicine (31 citations) and Modeling and Simulation (13 citations). Arash Kia has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Prem Timsina, Robert Freeman, Madhu Mazumdar, Matthew A. Levin, David L. Reich, Himanshu Joshi, Roopa Kohli‐Seth, Pranai Tandon, Eyal Klang and Kavita V. Dharmarajan. Their work appears in journals such as Journal of Clinical Medicine, Critical Care Medicine, JAMA Network Open, Journal of Human Nutrition and Dietetics and BMJ Supportive & Palliative Care.
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.