Neha Sharma

35 papers receiving 263 citations

Peers

Neha Sharma
Comparison fields: 5 of 99
  • Otorhinolaryngology 28
  • Health Information Management 25
  • Periodontics 15
  • Artificial Intelligence 102
  • Information Systems 55
Replace Zainab Abu Bakar with:
Zainab Abu Bakar Malaysia
Anurag Gupta India
Vassilis Tampakas Greece
Guadalupe Canahuate United States
Shereen Fouad United Kingdom
C. Gunavathi India
Julien Aligon France
Huaiguang Wu China
Ramjeevan Singh Thakur India
Neha Sharma relative to Zainab Abu Bakar Malaysia Zainab Abu Bakar's profile →
Citations per field
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Zainab Abu Bakar · 1×
Citations per year

Countries citing papers authored by Neha Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Neha Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201532
2 201528
3 201327
4 202119
5 202018
6 202117
7 201617
8
Magnitude of acute respiratory infections in under five.
199314
9 201313
10 201411
11 20149
12 20219
13 20147
14 20196
15 20235
16 20175
17 20145
18 20224
19 20084
20 20194

About Neha Sharma

Neha Sharma is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Management Information Systems and Computational Theory and Mathematics, having authored 38 papers that have together received 277 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (8 papers), Big Data and Business Intelligence (6 papers), Rough Sets and Fuzzy Logic (5 papers), Head and Neck Cancer Studies (3 papers), Imbalanced Data Classification Techniques (3 papers), Oral Health Pathology and Treatment (3 papers), Gene expression and cancer classification (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Otorhinolaryngology (28 citations), Health Information Management (25 citations), Periodontics (15 citations), Artificial Intelligence (102 citations) and Information Systems (55 citations). Neha Sharma has collaborated with scholars based in India, Romania and Israel. Frequent co-authors include Hari Om, Amlan Chakrabarti, Valentina Emilia Bălaş, Alfred M. Bruckstein⋆, Manoj Kumar Singh, Navneet Singh, Siddharth Sharma, Digamber Behera, Jan Martinovič and K.C. Nagpal. Their work appears in journals such as Developmental Neuroscience, Multimedia Tools and Applications, Cancer Epidemiology, Meccanica and International Journal of Advanced Intelligence Paradigms.

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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