Deepika Kumar

40 papers receiving 1.1k citations

Deepika Kumar's Hit Papers

Fake News Classification using transformer based enhanced LSTM and BERT 2022 · 107 citations
1070+1+3Years since publication50100150200250

Peers

Deepika Kumar
Comparison fields: 5 of 151
  • Health Information Management 203
  • Health Informatics 23
  • Artificial Intelligence 435
  • Computer Vision and Pattern Recognition 205
  • Radiology, Nuclear Medicine and Imaging 193
Replace Vimal K. Shrivastava with:
Vimal K. Shrivastava India
Yujia Li China
Anas Bilal China
Ioannis Kavakiotis Greece
Shagun Sharma India
Luca Saba Italy
Alhadi Bustamam Indonesia
Zahra Alizadeh Sani Iran
Joseph A. Cruz Canada
Deepika Kumar relative to Vimal K. Shrivastava India Vimal K. Shrivastava's profile →
Citations per field
00.5×3.8×
Vimal K. Shrivastava · 1×
Citations per year

Countries citing papers authored by Deepika Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Deepika Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier
Hit paper breakdown →
2021292
2 2015154
3 2020118
4
Fake News Classification using transformer based enhanced LSTM and BERT
Hit paper breakdown →
2022107
5 202092
6 200976
7 201841
8 202130
9 202219
10 202219
11 202318
12 202316
13 202114
14 202213
15 202113
16 201812
17 202011
18 202011
19 202111
20 202210

About Deepika Kumar

Deepika Kumar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oncology and Signal Processing, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), COVID-19 diagnosis using AI (6 papers), Brain Tumor Detection and Classification (4 papers), Digital Imaging for Blood Diseases (3 papers), Cutaneous Melanoma Detection and Management (3 papers), Artificial Intelligence in Healthcare (3 papers), Gene expression and cancer classification (3 papers) and Cancer Immunotherapy and Biomarkers (3 papers). The work is most often cited by research in Health Information Management (203 citations), Health Informatics (23 citations), Artificial Intelligence (435 citations), Computer Vision and Pattern Recognition (205 citations) and Radiology, Nuclear Medicine and Imaging (193 citations). Deepika Kumar has collaborated with scholars based in India, United States and Romania. Frequent co-authors include Mamta Mittal, Saloni Kumari, D. Jude Hemanth, Sudipta Roy, Nishant Rai, Mina L. Xu, Ahad Ali, A.P. Mittal, Suresh Chandra Satapathy and Nikita Jain. Their work appears in journals such as Electronics, Multimedia Tools and Applications, Frontiers in Oncology, Applied Sciences and Machine Vision and Applications.

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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