Mudit Agarwal

25 papers receiving 301 citations

Peers

Mudit Agarwal
Comparison fields: 5 of 93
  • Modeling and Simulation 40
  • Radiological and Ultrasound Technology 33
  • Medical Laboratory Technology 9
  • Statistics, Probability and Uncertainty 28
  • Otorhinolaryngology 15
Replace Sabine Hoffmann with:
Sabine Hoffmann Germany
Nour Shaheen Egypt
Rita Larsen‐Reindorf Ghana
Richard Nelson United States
Jessica E. Becker United States
Andro Košec Croatia
Liping Zhang China
Emma Lawrence United States
Minoru Kaneko Japan
Mudit Agarwal relative to Sabine Hoffmann Germany Sabine Hoffmann's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mudit Agarwal

Since Specialization
Citations

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

Fields of papers citing papers by Mudit Agarwal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200856
2 202055
3 201947
4 201643
5 202223
6 201917
7 201713
8 202010
9 20209
10 20208
11 19988
12 19976
13
The Clinical Characteristics of Coinfection of COVID19 and Influenza A Viruses - A Case Series.
20213
14 20222
15 19802
16 20222
17 20231
18 20211
19 20201
20 20211

About Mudit Agarwal

Mudit Agarwal is a scholar working on Surgery, Infectious Diseases, Epidemiology, Otorhinolaryngology and Pulmonary and Respiratory Medicine, having authored 30 papers that have together received 314 indexed citations. Recurring topics across this work include Bone Tumor Diagnosis and Treatments (4 papers), COVID-19 Clinical Research Studies (3 papers), Sarcoma Diagnosis and Treatment (3 papers), COVID-19 epidemiological studies (2 papers), Muscle and Compartmental Disorders (2 papers), Head and Neck Cancer Studies (2 papers), Sinusitis and nasal conditions (2 papers) and Vestibular and auditory disorders (2 papers). The work is most often cited by research in Modeling and Simulation (40 citations), Radiological and Ultrasound Technology (33 citations), Medical Laboratory Technology (9 citations), Statistics, Probability and Uncertainty (28 citations) and Otorhinolaryngology (15 citations). Mudit Agarwal has collaborated with scholars based in India, United States and Canada. Frequent co-authors include Carl E. Stafstrom, Michael V. Johnston, Pramod Kumar Pisharady, Umesh Kumar Singh, Suprakash Gupta, Deepika C Khakha, S Mahajan, Somesh Gupta, Mehak Arora and Ayush Lohiya. Their work appears in journals such as Frontiers in Pharmacology, Expert Review of Anti-infective Therapy, Frontiers in Immunology, Epidemiology and Infection and The Journal of Laryngology & Otology.

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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