Shikha Agrawal

2.7k citations
69 papers · 1.4k indexed · 1 hit paper · h-index 16

Shikha Agrawal

64 papers receiving 1.4k citations

Hit Papers

Survey on Anomaly Detection using Data Mining Techniques3932015202620182022100200300

Peers

Shikha Agrawal
Comparison fields: 5 of 146
  • Pharmaceutical Science 154
  • Computer Networks and Communications 417
  • Signal Processing 187
  • Artificial Intelligence 515
  • Molecular Medicine 67
Replace Mrinmoy Ghosh with:
Mrinmoy Ghosh South Korea
Qiuxia Chen China
Amit Srivastava India
Min Du China
Amandeep Kaur India
Wen‐Chuan Lee Taiwan
Pei Yang China
Liqian Zhou China
Jianjun Qi China
Kyeong Soo Kim South Korea
Shikha Agrawal relative to Mrinmoy Ghosh South Korea Mrinmoy Ghosh's profile →
Citations per field
00.5×3.3×
Mrinmoy Ghosh · 1×
Citations per year

Countries citing papers authored by Shikha Agrawal

Since Specialization
Citations

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

Fields of papers citing papers by Shikha Agrawal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20253
2 20250
3 20244
4 20246
5 20235
6 202268
7 20224
8 20229
9 202214
10
A Survey On Task Scheduling Algorithms In Cloud Computing
20205
11
An Efficient Approach Of Image Segmentation For Skin Cancer Detection
20192
12
A BRIEF REVIEW ON VARIOUS IMAGE SEGMENTATION TECHNIQUES FOR DETECTION OF ARTHRITIS
20180
13 20181
14 20171
15 20151
16 201548
17 20147
18
Formulation and evaluation of herbal cream containing extract of Ziziphus jujuba leaves for analgesic potential
20121
19 200425
20 200493

About Shikha Agrawal

Shikha Agrawal is a scholar working on Pharmaceutical Science, Biotechnology and Artificial Intelligence, having authored 69 papers that have together received 1.4k indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (8 papers), Prostate Cancer Treatment and Research (7 papers), Drug Solubulity and Delivery Systems (5 papers), Microbial Inactivation Methods (5 papers), Metaheuristic Optimization Algorithms Research (4 papers), Spam and Phishing Detection (3 papers), Network Security and Intrusion Detection (3 papers) and Data Mining Algorithms and Applications (3 papers). The work is most often cited by research in Pharmaceutical Science (154 citations), Computer Networks and Communications (417 citations) and Signal Processing (187 citations). Shikha Agrawal has collaborated with scholars based in India, Australia and Netherlands. Frequent co-authors include Jitendra Agrawal, Sanjay Silakari, Alok R. Ray, Sanjay Jain, Shyam S. Pancholi, Govind P. Agrawal, Phillip D. Stricker, James Thompson, Sanjeev Sharma and Anshu Sharma. Their work appears in journals such as Journal of Clinical Oncology, Scientific Reports and The Journal of Urology.

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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