Mohammad Bayat

151 papers receiving 2.7k citations

Peers

Mohammad Bayat
Comparison fields: 5 of 129
  • Rehabilitation 921
  • Radiology, Nuclear Medicine and Imaging 1.7k
  • Dermatology 476
  • Insect Science 433
  • Genetics 246
Replace Alena Ribeiro Alves Peixoto Medrado with:
Alena Ribeiro Alves Peixoto Medrado Brazil
Sufan Chien United States
Traci A. Wilgus United States
Dongqing Li China
Maria Witte Germany
Cheng‐Che E. Lan Taiwan
Mariarosaria Galeano Italy
Alan D. Widgerow United States
Philip V. Peplow New Zealand
Michael Schäffer Germany
Mohammad Bayat relative to Alena Ribeiro Alves Peixoto Medrado Brazil Alena Ribeiro Alves Peixoto Medrado's profile →
Citations per field
00.5×2.6×
Alena Ribeiro Alves Peixoto Medrado · 1×
Citations per year

Countries citing papers authored by Mohammad Bayat

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Bayat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohammad Bayat, 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 Mohammad Bayat Line = papers co-authored together Mohammad Bayat links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 156 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201680
2 201965
3 201260
4 200559
5 200856
6 201255
7 200652
8 200952
9 201851
10 202050
11 202047
12 202045
13 201943
14 200743
15 201842
16 202042
17 201342
18 201641
19 202041
20 202139

About Mohammad Bayat

Mohammad Bayat is a scholar working on Radiology, Nuclear Medicine and Imaging, Rehabilitation, Insect Science, Dermatology and Orthopedics and Sports Medicine, having authored 156 papers that have together received 2.8k indexed citations. Recurring topics across this work include Laser Applications in Dentistry and Medicine (107 papers), Wound Healing and Treatments (60 papers), Bee Products Chemical Analysis (36 papers), Dermatologic Treatments and Research (29 papers), Diabetic Foot Ulcer Assessment and Management (13 papers), Tendon Structure and Treatment (12 papers), Bone health and osteoporosis research (10 papers) and Mesenchymal stem cell research (9 papers). The work is most often cited by research in Rehabilitation (921 citations), Radiology, Nuclear Medicine and Imaging (1.7k citations), Dermatology (476 citations), Insect Science (433 citations) and Genetics (246 citations). Mohammad Bayat has collaborated with scholars based in Iran, United States and South Africa. Frequent co-authors include Abdollah Amini, Sufan Chien, Seyed Kamran Ghoreishi, Mohammad‐Amin Abdollahifar, Abbas Piryaei, Ramin Pouriran, Zhaleh Mohsenifar, Mohammad Esmaeelinejad, Fatemeh Zare and Ali Ezzati. Their work appears in journals such as Lasers in Medical Science, Photomedicine and Laser Surgery, Journal of Photochemistry and Photobiology B Biology, Journal of Cellular Biochemistry and The Journal of Rehabilitation Research and Development.

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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