Binod Thapa-Chhetry

13 papers receiving 398 citations

Peers

Binod Thapa-Chhetry
Comparison fields: 5 of 83
  • Health Informatics 10
  • Nephrology 43
  • Biological Psychiatry 13
  • Cognitive Neuroscience 84
  • Applied Psychology 16
Replace Srinivasan Vairavan with:
Srinivasan Vairavan United States
Franklin King United States
Maria Filippou-Frye United States
Ching-Feng Huang Taiwan
Ríona Mc Ardle United Kingdom
Redwan Maatoug France
Yi-han Sheu United States
Janice M. Ranson United Kingdom
Micah Cearns Australia
Erica N. Madero United States
Binod Thapa-Chhetry relative to Srinivasan Vairavan United States Srinivasan Vairavan's profile →
Citations per field
00.5×2.6×
Srinivasan Vairavan · 1×
Citations per year

Countries citing papers authored by Binod Thapa-Chhetry

Since Specialization
Citations

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

Fields of papers citing papers by Binod Thapa-Chhetry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Binod Thapa-Chhetry. 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 Binod Thapa-Chhetry. The network helps show where Binod Thapa-Chhetry may publish in the future.

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2021127
2 201466
3 201762
4 201341
5 201933
6 202123
7 202014
8 20229
9 20209
10 20195
11 20234
12 20214
13 20193

About Binod Thapa-Chhetry

Binod Thapa-Chhetry is a scholar working on General Health Professions, Physiology, Pathology and Forensic Medicine, Computer Vision and Pattern Recognition and Nephrology, having authored 13 papers that have together received 400 indexed citations. Recurring topics across this work include Mobile Health and mHealth Applications (4 papers), Physical Activity and Health (4 papers), Spinal Cord Injury Research (2 papers), Context-Aware Activity Recognition Systems (2 papers), Cardiovascular and exercise physiology (1 paper), Data Visualization and Analytics (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Bipolar Disorder and Treatment (1 paper). The work is most often cited by research in Health Informatics (10 citations), Nephrology (43 citations), Biological Psychiatry (13 citations), Cognitive Neuroscience (84 citations) and Applied Psychology (16 citations). Binod Thapa-Chhetry has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Stephen Intille, Christopher J. L. Newth, Vinay Vaidya, Ting Feng, David Inwald, Junzi Dong, Ramin V. Parsey, J. John Mann, M. Elizabeth Sublette and María A. Oquendo. Their work appears in journals such as Medicine & Science in Sports & Exercise, Journal of Psychiatric Research, PLoS ONE, Critical Care and Journal of Affective Disorders.

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.

Explore authors with similar magnitude of impact