Rahmatollah Beheshti

558 citations
32 papers · 307 indexed · h-index 10
Topics
Machine Learning in Healthcare (8 papers)Artificial Intelligence in Healthcare (8 papers)Obesity, Physical Activity, Diet (5 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEJournal of Nutrition
Partner nations
United StatesIranUganda

In The Last Decade

Rahmatollah Beheshti

30 papers receiving 295 citations

Peers

Rahmatollah Beheshti
Comparison fields: 5 of 92
  • Artificial Intelligence 117
  • Public Health, Environmental and Occupational Health 74
  • Health Information Management 64
  • General Health Professions 34
  • Health Informatics 28
Replace Jae Min with:
Jae Min United States
Taqdir Ali South Korea
Samah Fodeh United States
Martin Gerdes Norway
Oladimeji Farri United States
Helen Rostill United Kingdom
Nimit S. Sohoni United States
Arlene Oetomo Canada
Elena Villalba‐Mora Spain
Avesh Kumar Singh India
Rahmatollah Beheshti relative to Jae Min United States Jae Min's profile →
Citations per field
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Citations per year

Countries citing papers authored by Rahmatollah Beheshti

Since Specialization
Citations

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

Fields of papers citing papers by Rahmatollah Beheshti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rahmatollah Beheshti

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 1
4 3
5 36
6 6
7
Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records.
6
8 5
9 9
10 8
11 24
12 4
13 10
14 26
15 20
16 1
17 6
18 6
19 8
20 2

About Rahmatollah Beheshti

Rahmatollah Beheshti is a scholar working on Health Information Management, Health Informatics and General Decision Sciences, having authored 32 papers that have together received 307 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (8 papers), Artificial Intelligence in Healthcare (8 papers) and Obesity, Physical Activity, Diet (5 papers). The work is most often cited by research in Health Informatics (28 citations), Health Information Management (64 citations) and Artificial Intelligence (117 citations). Rahmatollah Beheshti has collaborated with scholars based in United States, Iran and Uganda. Frequent co-authors include Thao-Ly T. Phan, Gita Sukthankar, Takeru Igusa, Jessica C. Jones‐Smith, Mehdi Jalalpour, Thomas A. Glass, Randi E. Foraker, H. Timothy Bunnell, James R. Langabeer and Yosef Khan. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Nutrition.

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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