Deepak Kumar

885 citations
70 papers · 613 · h-index 11

Impact in

  • Epidemiology top 10%
    • Preterm Birth and Chorioamnionitis
    • Virology and Viral Diseases
    • Mycobacterium research and diagnosis
    • Cervical Cancer and HPV Research
    • Acute Kidney Injury Research

Papers in

Deepak Kumar

50 papers receiving 579 citations

Peers

Deepak Kumar
Comparison fields: 5 of 89
  • Epidemiology 327
  • Nephrology 25
  • Infectious Diseases 46
  • Endocrinology, Diabetes and Metabolism 36
  • Obstetrics and Gynecology 18
Replace Haijian He with:
Haijian He China
Lynne Sykes United Kingdom
Yining He China
Heather A. Paich United States
Weera Mahavanakul Thailand
Aikaterini Spyridaki Greece
Xinjing Wang China
Fazılet Duygu Türkiye
Marcelo Magalhães Brazil
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Citations per field
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Citations per year

Countries citing papers authored by Deepak Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013115
2 200679
3 201176
4 200675
5 201856
6 201829
7 201722
8 202319
9 202116
10 202313
11 202312
12 20218
13 20218
14 20218
15 20187
16 20237
17 20247
18 20125
19 20245
20 20245

About Deepak Kumar

Deepak Kumar is a scholar working on Endocrinology, Diabetes and Metabolism, Epidemiology, Modeling and Simulation, Health Information Management and Obstetrics and Gynecology, having authored 70 papers that have together received 613 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (6 papers), Diabetes Management and Research (4 papers), Artificial Intelligence in Healthcare (4 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Preterm Birth and Chorioamnionitis (3 papers), Virology and Viral Diseases (3 papers), Acute Kidney Injury Research (2 papers) and Pancreatic function and diabetes (2 papers). The work is most often cited by research in Epidemiology (327 citations), Nephrology (25 citations), Infectious Diseases (46 citations), Endocrinology, Diabetes and Metabolism (36 citations) and Obstetrics and Gynecology (18 citations). Deepak Kumar has collaborated with scholars based in India, United States and Pakistan. Frequent co-authors include Diwakar D. Kulkarni, Chakradhar Tosh, Kuldeep Dhama, Brian M. Mercer, Joseph M. Mansour, Jennifer M. Fox, Ruchi Tiwari, Mahesh Mahendran, Shoor Vir Singh and Shambhu Dayal Singh. Their work appears in journals such as Journal of Perinatology, Proteins Structure Function and Bioinformatics, Journal of Drug Delivery Science and Technology, Pediatric Nephrology and Annals of Noninvasive Electrocardiology.

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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