Neha Shah

10.2k citations
92 papers · 3.6k indexed · 1 hit paper · h-index 27

Neha Shah

88 papers receiving 3.5k citations

Hit Papers

Characterizing a model human gut microbiota composed of m...5592009202620142020100200300400500

Peers

Neha Shah
Comparison fields: 5 of 155
  • Infectious Diseases 2.5k
  • Epidemiology 2.0k
  • Endocrinology 180
  • Molecular Medicine 127
  • Applied Microbiology and Biotechnology 43
Replace Amita Jain with:
Amita Jain India
Philippe Glaziou Switzerland
Fehmı Tabak Türkiye
Gibson Kibiki Tanzania
Dinesh Mondal Bangladesh
Nazir Ismail South Africa
Reşat Özaras Türkiye
Ruth McNerney United Kingdom
Mohammad Javad Nasiri Iran
Suhail Ahmad Kuwait
Neha Shah relative to Amita Jain India Amita Jain's profile →
Citations per field
00.5×
Amita Jain · 1×
Citations per year

Countries citing papers authored by Neha Shah

Since Specialization
Citations

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

Fields of papers citing papers by Neha Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20260
2 20250
3 20242
4 20241
5 20239
6 20232
7 20234
8 20206
9 20202
10 20204
11 201719
12 20173
13 20161
14 201511
15
Impact of a shortage of first-line antituberculosis medication on tuberculosis control - United States, 2012-2013.
201320
16 201141
17 2009245
18
Population-based chest X-ray screening for pulmonary tuberculosis in people living with HIV/AIDS, An Giang, Vietnam.
200821
19 200732
20 199923

About Neha Shah

Neha Shah is a scholar working on Infectious Diseases, Epidemiology and Surgery, having authored 92 papers that have together received 3.6k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (63 papers), Pneumocystis jirovecii pneumonia detection and treatment (31 papers), Mycobacterium research and diagnosis (25 papers), Pneumonia and Respiratory Infections (19 papers), Infectious Diseases and Tuberculosis (18 papers), HIV/AIDS Research and Interventions (15 papers), Diagnosis and treatment of tuberculosis (13 papers) and HIV, Drug Use, Sexual Risk (7 papers). The work is most often cited by research in Infectious Diseases (2.5k citations), Epidemiology (2.0k citations) and Endocrinology (180 citations). Neha Shah has collaborated with scholars based in United States, South Africa and Kenya. Frequent co-authors include Neel R. Gandhi, Anthony P. Moll, Jason R. Andrews, Gerald Friedland, Barun Mathema, Darren Weissman, Richard K. Wilson, Aye Wollam, Robert S. Fulton and Prashini Moodley. Their work appears in journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and The Lancet.

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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