Deepesh Agarwal

520 citations
24 papers · 349 indexed · h-index 7

Impact in

    • Food Allergy and Anaphylaxis Research
    • Allergic Rhinitis and Sensitization
  • Food Science top 10%
    • Proteins in Food Systems
    • Probiotics and Fermented Foods

Papers in

    • Machine Learning and Algorithms 5
    • Advanced Graph Neural Networks 3
    • Data Stream Mining Techniques 3
    • Machine Learning and Data Classification 2
    • Advanced biosensing and bioanalysis techniques 2

Deepesh Agarwal

21 papers receiving 339 citations

Peers

Deepesh Agarwal
Comparison fields: 5 of 98
  • Immunology and Allergy 110
  • Food Science 85
  • Clinical Biochemistry 27
  • Emergency Medicine 26
  • Dermatology 20
Replace Keunpyo Kim with:
Keunpyo Kim United States
Xiangqun Liu China
Jinghua Zhong China
Yiwei Liu China
Nan Bao China
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Samarjit Roy India
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Citations per field
00.5×6.8×
Keunpyo Kim · 1×
Citations per year

Countries citing papers authored by Deepesh Agarwal

Since Specialization
Citations

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

Fields of papers citing papers by Deepesh Agarwal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009155
2 202368
3 201643
4 202217
5 202414
6 202212
7 20219
8 20165
9 20234
10 20204
11 20223
12 20252
13 20232
14 20152
15 20222
16 20232
17 20221
18 20241
19
Percuteneous mitral balloon valvuloplasty in patients with post surgical mitral restenosis: result of 70 cases.
20111
20 20221

About Deepesh Agarwal

Deepesh Agarwal is a scholar working on Artificial Intelligence, Molecular Biology, Control and Systems Engineering, Mechanical Engineering and Electrical and Electronic Engineering, having authored 24 papers that have together received 349 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (5 papers), Advanced Graph Neural Networks (3 papers), Data Stream Mining Techniques (3 papers), Machine Fault Diagnosis Techniques (2 papers), Machine Learning and Data Classification (2 papers), Advanced Memory and Neural Computing (2 papers), Advanced biosensing and bioanalysis techniques (2 papers) and Green IT and Sustainability (2 papers). The work is most often cited by research in Immunology and Allergy (110 citations), Food Science (85 citations), Clinical Biochemistry (27 citations), Emergency Medicine (26 citations) and Dermatology (20 citations). Deepesh Agarwal has collaborated with scholars based in United States, India and France. Frequent co-authors include Balasubramaniam Natarajan, Jean‐Charles Gaudin, Asghar Taheri‐Kafrani, Jean‐Marc Chobert, Thomas Haertlé, Hanitra Rabesona, Abdol‐Khalegh Bordbar, Claudia Nioi, Laya Das and Sai Munikoti. Their work appears in journals such as Information Sciences, Computers & Chemical Engineering, iScience, IEEE Transactions on Neural Networks and Learning Systems and Cells.

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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