Divya Tomar

1.5k citations
41 papers · 1.2k · 1 hit paper · h-index 15

Impact in

Papers in

Divya Tomar

40 papers receiving 1.1k citations

Divya Tomar's Hit Papers

A survey on Data Mining approaches for Healthcare 2013 · 373 citations
3730+4+8Years since publication100200300

Peers

Divya Tomar
Comparison fields: 5 of 132
  • Health Information Management 298
  • Software 87
  • Artificial Intelligence 557
  • Computer Vision and Pattern Recognition 251
  • Information Systems 247
Replace Sultan Aljahdali with:
Sultan Aljahdali Saudi Arabia
Hang Yu China
F. M. Javed Mehedi Shamrat Bangladesh
Murat Karabatak Türkiye
Bo Jin China
Jawad Rasheed Türkiye
Ayush Goyal India
Sachin Ahuja India
H. Altay Güvenir Türkiye
Daya Gupta India
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Citations per year

Countries citing papers authored by Divya Tomar

Since Specialization
Citations

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

Fields of papers citing papers by Divya Tomar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Divya Tomar, 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 Divya Tomar Line = papers co-authored together Divya Tomar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A survey on Data Mining approaches for Healthcare
Hit paper breakdown →
2013373
2 2015130
3 201595
4 201477
5 201258
6 201547
7 201645
8 201441
9 201428
10 201428
11 201327
12 201526
13 201421
14 201421
15 201614
16 201413
17 201413
18 201613
19 201411
20 201410

About Divya Tomar

Divya Tomar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Health Information Management and Control and Systems Engineering, having authored 41 papers that have together received 1.2k indexed citations. Recurring topics across this work include Face and Expression Recognition (9 papers), Text and Document Classification Technologies (9 papers), Imbalanced Data Classification Techniques (8 papers), Artificial Intelligence in Healthcare (6 papers), Data Mining Algorithms and Applications (4 papers), Software Engineering Research (4 papers), Advanced Algorithms and Applications (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Health Information Management (298 citations), Software (87 citations), Artificial Intelligence (557 citations), Computer Vision and Pattern Recognition (251 citations) and Information Systems (247 citations). Divya Tomar has collaborated with scholars based in India and Israel. Frequent co-authors include Sonali Agarwal, Akhilesh Kumar Yadav, Sankalp Verma, Shubham Singhal, Ravi Prakash Sasankoti Mohan, Shipra Jaidka, Shikha Singh and Sonal Agarwal. Their work appears in journals such as Indian Journal of Science and Technology, Knowledge-Based Systems, Egyptian Informatics Journal, International Journal of Computational Intelligence Systems and Journal of Oral Science.

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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