Vimbi Viswan

657 total citations · 1 hit paper
12 papers, 298 citations indexed

About

Vimbi Viswan is a scholar working on Artificial Intelligence, Neurology and Health Information Management. According to data from OpenAlex, Vimbi Viswan has authored 12 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 5 papers in Neurology and 4 papers in Health Information Management. Recurrent topics in Vimbi Viswan's work include Machine Learning in Healthcare (5 papers), Brain Tumor Detection and Classification (5 papers) and Artificial Intelligence in Healthcare (4 papers). Vimbi Viswan is often cited by papers focused on Machine Learning in Healthcare (5 papers), Brain Tumor Detection and Classification (5 papers) and Artificial Intelligence in Healthcare (4 papers). Vimbi Viswan collaborates with scholars based in United Kingdom, Oman and Saudi Arabia. Vimbi Viswan's co-authors include Mufti Mahmud, Noushath Shaffi, Faizal Hajamohideen, S. Karthikeyan, Abdelhamid Abdesselam, Subramanian Karthikeyan, M. Shamim Kaiser, V. N. Manjunath Aradhya, Shuqiang Wang and Srinivasa Rao Sirasanagandla and has published in prestigious journals such as International Journal of Neural Systems, Cognitive Computation and Brain Informatics.

In The Last Decade

Vimbi Viswan

10 papers receiving 282 citations

Hit Papers

align trajectories

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.

Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer’s disease detection

2024 134 citations Vimbi Viswan, Noushath Shaffi et al. Brain Informatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vimbi Viswan United Kingdom	6	131	77	49	45	40	12	298
Faizal Hajamohideen United Kingdom	5	78 0.6×	65 0.8×	26 0.5×	29 0.6×	18 0.5×	17	175
Vinodhini Mani India	7	116 0.9×	88 1.1×	25 0.5×	73 1.6×	13 0.3×	12	343
Deevyankar Agarwal Spain	6	182 1.4×	78 1.0×	185 3.8×	24 0.5×	37 0.9×	10	413
Xinyan Zhao China	5	110 0.8×	123 1.6×	39 0.8×	39 0.9×	8 0.2×	9	313
Yogesh Kumar Rathore India	9	61 0.5×	96 1.2×	33 0.7×	49 1.1×	11 0.3×	29	278
Dan Pan China	8	187 1.4×	186 2.4×	72 1.5×	69 1.5×	20 0.5×	28	474
Paul Hager Germany	6	110 0.8×	31 0.4×	85 1.7×	22 0.5×	98 2.5×	9	345
Akshay Pai Denmark	8	95 0.7×	109 1.4×	89 1.8×	28 0.6×	10 0.3×	28	356
Khansa Rasheed Pakistan	4	96 0.7×	15 0.2×	38 0.8×	33 0.7×	37 0.9×	4	287
Wenyong Zhu China	4	168 1.3×	163 2.1×	72 1.5×	40 0.9×	6 0.1×	5	334

Countries citing papers authored by Vimbi Viswan

Since Specialization

Citations

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

Fields of papers citing papers by Vimbi Viswan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vimbi Viswan

This figure shows the co-authorship network connecting the top 25 collaborators of Vimbi Viswan. A scholar is included among the top collaborators of Vimbi Viswan 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 Vimbi Viswan. Vimbi Viswan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

1.

Viswan, Vimbi, Noushath Shaffi, Srinivasa Rao Sirasanagandla, et al.. (2025). Application of Explainable Artificial Intelligence in Autism Spectrum Disorder Detection. Cognitive Computation. 17(3).

2.

Shaffi, Noushath, Vimbi Viswan, & Mufti Mahmud. (2024). Ensemble of vision transformer architectures for efficient Alzheimer’s Disease classification. Brain Informatics. 11(1). 25–25. 5 indexed citations

3.

Karthikeyan, S., Faizal Hajamohideen, Vimbi Viswan, Noushath Shaffi, & Mufti Mahmud. (2024). Exploring Intervention Techniques for Alzheimer’s Disease: Conventional Methods and the Role of AI in Advancing Care. 2(2). 59–77. 7 indexed citations

4.

Shaffi, Noushath, Vimbi Viswan, & Mufti Mahmud. (2024). VisTAD: A Vision Transformer Pipeline for the Classification of Alzheimer’s Disease. 1–8.

5.

Viswan, Vimbi, Noushath Shaffi, & Mufti Mahmud. (2024). Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer’s disease detection. Brain Informatics. 11(1). 10–10. 134 indexed citations breakdown →

6.

Shaffi, Noushath, S. Karthikeyan, Vimbi Viswan, et al.. (2024). Performance Evaluation of Deep, Shallow and Ensemble Machine Learning Methods for the Automated Classification of Alzheimer’s Disease. International Journal of Neural Systems. 34(7). 2450029–2450029. 12 indexed citations

7.

Hajamohideen, Faizal, Noushath Shaffi, Mufti Mahmud, et al.. (2023). Four-way classification of Alzheimer’s disease using deep Siamese convolutional neural network with triplet-loss function. Brain Informatics. 10(1). 5–5. 55 indexed citations

8.

Shaffi, Noushath, Vimbi Viswan, Mufti Mahmud, Faizal Hajamohideen, & Subramanian Karthikeyan. (2023). Multi-Planar MRI-Based Classification of Alzheimer's Disease Using Tree-Based Machine Learning Algorithms*. 496–502. 2 indexed citations

9.

Viswan, Vimbi, Noushath Shaffi, Mufti Mahmud, S. Karthikeyan, & Faizal Hajamohideen. (2023). Explainable Artificial Intelligence in Alzheimer’s Disease Classification: A Systematic Review. Cognitive Computation. 16(1). 1–44. 72 indexed citations

10.

Shaffi, Noushath, Vimbi Viswan, Mufti Mahmud, Faizal Hajamohideen, & Subramanian Karthikeyan. (2023). Towards Automated Classification of Parkinson's Disease: Comparison of Machine Learning Methods using MRI and Acoustic Data. 2 indexed citations

11.

Viswan, Vimbi, Noushath Shaffi, Mufti Mahmud, S. Karthikeyan, & Faizal Hajamohideen. (2023). A Comparative Study of Pretrained Deep Neural Networks for Classifying Alzheimer's and Parkinson's Disease. 1334–1339. 3 indexed citations

12.

Viswan, Vimbi, Noushath Shaffi, Mufti Mahmud, S. Karthikeyan, & Faizal Hajamohideen. (2023). Application of Explainable Artificial Intelligence in Alzheimer's Disease Classification: A Systematic Review. Research Square. 6 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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