John Tazare

15 papers receiving 390 citations

John Tazare's Hit Papers

Glucagon-like peptide-1 receptor agonists, but not dipeptidyl peptidase-4 inhibitors, reduce alcohol intake 2025 · 24 citations
240Years since publication5101520

Peers

John Tazare
Comparison fields: 5 of 67
  • Obstetrics and Gynecology 67
  • Health 74
  • Genetics 79
  • Statistics and Probability 21
  • Microbiology 15
Replace F. Belmonte with:
F. Belmonte Denmark
Tomomi Egawa‐Takata Japan
Adam Lee United States
Gábor Szabó Hungary
Laura Sarno Italy
Laureen Ribassin-Majed France
T.G. Hopkins United Kingdom
Maria Fernanda Brandão de Resende Guimarães Brazil
Thawalwong Ratanasiri Thailand
Diego Torres‐Carranza Spain
John Tazare relative to F. Belmonte Denmark F. Belmonte's profile →
Citations per field
00.5×7.4×
F. Belmonte · 1×
Citations per year

Countries citing papers authored by John Tazare

Since Specialization
Citations

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

Fields of papers citing papers by John Tazare

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2020157
2 2022130
3
Glucagon-like peptide-1 receptor agonists, but not dipeptidyl peptidase-4 inhibitors, reduce alcohol intake
Hit paper breakdown →
202524
4 202121
5 202216
6 20209
7 20238
8 20247
9 20246
10 20244
11 20233
12 20233
13 20242
14 20241
15 20241
16 20240
17 20240
18 20240
19 20240

About John Tazare

John Tazare is a scholar working on Statistics and Probability, Cardiology and Cardiovascular Medicine, Epidemiology, Economics and Econometrics and Infectious Diseases, having authored 19 papers that have together received 392 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (3 papers), Atrial Fibrillation Management and Outcomes (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Liver Diseases and Immunity (1 paper), Neuroendocrine Tumor Research Advances (1 paper), Statistical Methods in Clinical Trials (1 paper) and Meta-analysis and systematic reviews (1 paper). The work is most often cited by research in Obstetrics and Gynecology (67 citations), Health (74 citations), Genetics (79 citations), Statistics and Probability (21 citations) and Microbiology (15 citations). John Tazare has collaborated with scholars based in United Kingdom, United States and Hong Kong. Frequent co-authors include Pauline Paterson, Heidi J. Larson, R Matthew Chico, Eliz Kilich, Sara Dada, Mark R. Francis, Sebastian Brandner, Paul Mulholland, John Gregson and Diego Ottaviani. Their work appears in journals such as Pharmacoepidemiology and Drug Safety, BMC Medicine, Cancers, The Journals of Gerontology Series A and British Journal of Clinical Pharmacology.

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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