Basu Dev Shivahare

876 total citations · 2 hit papers
32 papers, 365 citations indexed

About

Basu Dev Shivahare is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Neurology. According to data from OpenAlex, Basu Dev Shivahare has authored 32 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 6 papers in Neurology. Recurrent topics in Basu Dev Shivahare's work include Brain Tumor Detection and Classification (6 papers), Artificial Intelligence in Healthcare (5 papers) and Metaheuristic Optimization Algorithms Research (5 papers). Basu Dev Shivahare is often cited by papers focused on Brain Tumor Detection and Classification (6 papers), Artificial Intelligence in Healthcare (5 papers) and Metaheuristic Optimization Algorithms Research (5 papers). Basu Dev Shivahare collaborates with scholars based in India, Saudi Arabia and Afghanistan. Basu Dev Shivahare's co-authors include Sandeep Kumar Mathivanan, Hariharan Rajadurai, Mohd Asif Shah, Saravanan Srinivasan, Prabhishek Singh, Manoj Diwakar, Vimal Bibhu, Saurav Mallik, Hong Qin and Shivani Gupta and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Basu Dev Shivahare

27 papers receiving 352 citations

Hit Papers

Employing deep learning and transfer learning for accurat... 2024 2026 2025 2024 2024 20 40 60
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Employing deep learning and transfer learning for accurate brain tumor detection
    2024 65 citations Sandeep Kumar Mathivanan, Hariharan Rajadurai et al. Scientific Reports profile →
  2. A hybrid deep CNN model for brain tumor image multi-classification
    2024 51 citations Saravanan Srinivasan, Sandeep Kumar Mathivanan et al. BMC Medical Imaging profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Basu Dev Shivahare India 10 118 116 107 72 29 32 365
Saravanan Alagarsamy India 11 99 0.8× 82 0.7× 121 1.1× 86 1.2× 13 0.4× 36 294
Loc Tran United States 10 129 1.1× 147 1.3× 161 1.5× 139 1.9× 36 1.2× 37 498
Awal Halifa Ghana 8 153 1.3× 103 0.9× 133 1.2× 71 1.0× 32 1.1× 12 335
Omar Hisham Alsadoon Iraq 11 67 0.6× 149 1.3× 129 1.2× 83 1.2× 34 1.2× 37 375
Bless Lord Y. Agbley China 12 88 0.7× 174 1.5× 64 0.6× 95 1.3× 18 0.6× 26 378
T. Rajendran India 10 66 0.6× 89 0.8× 87 0.8× 72 1.0× 33 1.1× 22 324
Balajee Maram India 9 78 0.7× 109 0.9× 108 1.0× 78 1.1× 19 0.7× 65 334
Sonali Dash India 15 82 0.7× 106 0.9× 206 1.9× 139 1.9× 46 1.6× 37 446
J. Anitha India 10 101 0.9× 96 0.8× 147 1.4× 66 0.9× 25 0.9× 26 408
Vibhav Prakash Singh India 14 66 0.6× 198 1.7× 207 1.9× 99 1.4× 14 0.5× 56 511

Countries citing papers authored by Basu Dev Shivahare

Since Specialization
Citations

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

Fields of papers citing papers by Basu Dev Shivahare

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Basu Dev Shivahare. 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 Basu Dev Shivahare. The network helps show where Basu Dev Shivahare may publish in the future.

Co-authorship network of co-authors of Basu Dev Shivahare

This figure shows the co-authorship network connecting the top 25 collaborators of Basu Dev Shivahare. A scholar is included among the top collaborators of Basu Dev Shivahare based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Basu Dev Shivahare. Basu Dev Shivahare is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Mathivanan, Sandeep Kumar, et al.. (2025). A multimodal machine learning model for bipolar disorder mania classification: Insights from acoustic, linguistic, and visual cues. Intelligence-Based Medicine. 11. 100223–100223.
3.
Mathivanan, Sandeep Kumar, et al.. (2024). A comprehensive health assessment approach using ensemble deep learning model for remote patient monitoring with IoT. Scientific Reports. 14(1). 15661–15661. 9 indexed citations
4.
Singh, Mukund Pratap, Jagendra Singh, Vinayakumar Ravi, et al.. (2024). A Healthcare System Employing Lightweight CNN for Disease Prediction with Artificial Intelligence. The Open Public Health Journal. 17(1). 9 indexed citations
5.
Srinivasan, Saravanan, et al.. (2024). Detection of Parkinson disease using multiclass machine learning approach. Scientific Reports. 14(1). 13813–13813. 32 indexed citations
6.
Mathivanan, Sandeep Kumar, et al.. (2024). Automated brain tumor diagnostics: Empowering neuro-oncology with deep learning-based MRI image analysis. PLoS ONE. 19(8). e0306493–e0306493. 5 indexed citations
7.
Singh, Mukund Pratap, Jagendra Singh, Vinayakumar Ravi, et al.. (2024). Impact and Implications of Quantum Computing on Blockchain-based Electronic Health Record Systems. 17(1). 5 indexed citations
8.
Bibhu, Vimal, et al.. (2024). Analysis of security and privacy challenges of smart health and sensing systems. Results in Engineering. 24. 103466–103466. 3 indexed citations
9.
Shivahare, Basu Dev & Radha Raman Chandan. (2024). Machine Learning Algorithms for Image Classification: A Comparative Review. 12(1,2). 1–8.
10.
Mathivanan, Sandeep Kumar, et al.. (2024). Employing deep learning and transfer learning for accurate brain tumor detection. Scientific Reports. 14(1). 7232–7232. 65 indexed citations breakdown →
11.
Srinivasan, Saravanan, et al.. (2024). A hybrid deep CNN model for brain tumor image multi-classification. BMC Medical Imaging. 24(1). 21–21. 51 indexed citations breakdown →
12.
Sunaina, Sunaina, et al.. (2024). Exploring Machine Learning to Predict Brain Tumour Disease. 195–199.
13.
Kumar, Umesh, et al.. (2023). Image Watermarking Techniques and Applications. 2. 1–4.
14.
Shivahare, Basu Dev, et al.. (2023). Medical Image Denoising and Brain Tumor Detection Using CNN and U-Net. 1–5. 6 indexed citations
15.
Shubham, Shubham, et al.. (2023). Cyber Crime Prevention and Techniques: A Comprehensive Survey. 1–4. 1 indexed citations
16.
Mathivanan, Sandeep Kumar, et al.. (2023). An enhanced multimodal fusion deep learning neural network for lung cancer classification. SHILAP Revista de lepidopterología. 6. 200068–200068. 41 indexed citations
17.
18.
Shivahare, Basu Dev, et al.. (2022). Survey Paper: Comparative Study of Machine Learning Techniques and its Recent Applications. 449–454. 18 indexed citations
19.
Shivahare, Basu Dev, et al.. (2021). Survey Paper: Whale optimization algorithm and its variant applications. 77–82. 26 indexed citations
20.
Shivahare, Basu Dev, et al.. (2019). Multilevel Thresholding based Image Segmentation using Whale Optimization Algorithm. International Journal of Innovative Technology and Exploring Engineering. 8(12). 4602–4613. 7 indexed citations

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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