A. Sheik Abdullah

561 total citations
52 papers, 220 citations indexed

About

A. Sheik Abdullah is a scholar working on Artificial Intelligence, Health Information Management and Computer Vision and Pattern Recognition. According to data from OpenAlex, A. Sheik Abdullah has authored 52 papers receiving a total of 220 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 15 papers in Health Information Management and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in A. Sheik Abdullah's work include Artificial Intelligence in Healthcare (15 papers), Imbalanced Data Classification Techniques (8 papers) and Online Learning and Analytics (5 papers). A. Sheik Abdullah is often cited by papers focused on Artificial Intelligence in Healthcare (15 papers), Imbalanced Data Classification Techniques (8 papers) and Online Learning and Analytics (5 papers). A. Sheik Abdullah collaborates with scholars based in India, Malaysia and United States. A. Sheik Abdullah's co-authors include S. Selvakumar, R. R. Rajalaxmi, P. Karthikeyan, R. Suganya, Murali Venkatesh, S. Rajaram, S. Geetha, A. M. Abirami, Utkarsh Mishra and Vinod Kumar and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Applied Soft Computing.

In The Last Decade

A. Sheik Abdullah

44 papers receiving 203 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Sheik Abdullah India 8 100 86 24 22 19 52 220
Faiz Ali Shah Estonia 8 126 1.3× 105 1.2× 8 0.3× 23 1.0× 63 3.3× 12 260
A Prathik India 5 73 0.7× 34 0.4× 7 0.3× 21 1.0× 28 1.5× 7 172
Mohammad Moshawrab Canada 6 114 1.1× 35 0.4× 7 0.3× 11 0.5× 23 1.2× 10 245
Ali Raad Lebanon 6 114 1.1× 35 0.4× 7 0.3× 11 0.5× 23 1.2× 14 251
Nahed Sharmen Bangladesh 7 69 0.7× 35 0.4× 3 0.1× 15 0.7× 19 1.0× 9 191
Yar Muhammad Pakistan 5 107 1.1× 114 1.3× 5 0.2× 26 1.2× 56 2.9× 9 285
Koushick Barua Bangladesh 6 57 0.6× 20 0.2× 3 0.1× 17 0.8× 20 1.1× 7 181
Lambodar Jena India 7 46 0.5× 16 0.2× 5 0.2× 28 1.3× 19 1.0× 17 147
Momina Shaheen Pakistan 7 138 1.4× 12 0.1× 12 0.5× 16 0.7× 51 2.7× 30 234
Kailas Devadkar India 6 141 1.4× 166 1.9× 3 0.1× 24 1.1× 75 3.9× 30 349

Countries citing papers authored by A. Sheik Abdullah

Since Specialization
Citations

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

Fields of papers citing papers by A. Sheik Abdullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Sheik Abdullah. 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 A. Sheik Abdullah. The network helps show where A. Sheik Abdullah may publish in the future.

Co-authorship network of co-authors of A. Sheik Abdullah

This figure shows the co-authorship network connecting the top 25 collaborators of A. Sheik Abdullah. A scholar is included among the top collaborators of A. Sheik Abdullah 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 A. Sheik Abdullah. A. Sheik Abdullah 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.
Abdullah, A. Sheik, et al.. (2025). Leveraging deep learning for enhanced diagnosis of autism spectrum disorder using resting-state functional magnetic resonance imaging and clinical data. Results in Engineering. 25. 104444–104444. 1 indexed citations
2.
Abdullah, A. Sheik, et al.. (2025). A diagnostic model for evaluating the posture recognition using multivariate Gaussian deep CNN for determining musculoskeletal disorders. Multimedia Tools and Applications. 84(41). 49635–49673.
3.
Geetha, S., et al.. (2025). UWE-Net: A Deep Learning Framework for Underwater Image Enhancement Integrating CBAM and Charbonnier Loss. Procedia Computer Science. 258. 689–698. 1 indexed citations
4.
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Abdullah, A. Sheik, et al.. (2025). Optimizing Requirements Engineering for Sustainable E-Learning Systems. 1–6. 1 indexed citations
6.
Karthikeyan, P., et al.. (2024). Enhancing personalized learning with explainable AI: A chaotic particle swarm optimization based decision support system. Applied Soft Computing. 156. 111451–111451. 10 indexed citations
7.
8.
Abdullah, A. Sheik, et al.. (2024). Enabling Technology Integrated Learning for Autistic Children Using Augmented Reality Based Cognitive Rehabilitation. SN Computer Science. 5(1). 3 indexed citations
9.
Quadir, Abdul, et al.. (2024). Enabling business sustainability for stock market data using machine learning and deep learning approaches. Annals of Operations Research. 342(1). 287–322. 3 indexed citations
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12.
Karthikeyan, P., et al.. (2024). Enhancing Educational Assessment: Predicting and Visualizing Student Performance using EDA and Machine Learning Techniques. Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation. 37(IS2). 240–245. 2 indexed citations
13.
Karthikeyan, P., et al.. (2023). Predicting academic performance of learners with the three domains of learning data using neuro-fuzzy model and machine learning algorithms. Journal of Engineering Research. 12(3). 397–411. 9 indexed citations
14.
15.
Abdullah, A. Sheik. (2022). Assessment of the risk factors of type II diabetes using ACO with self-regulative update function and decision trees by evaluation from Fisher’s Z-transformation. Medical & Biological Engineering & Computing. 60(5). 1391–1415. 6 indexed citations
16.
Abdullah, A. Sheik, S. Selvakumar, & Murali Venkatesh. (2021). Assessment and evaluation of CHD risk factors using weighted ranked correlation and regression with data classification. Soft Computing. 25(6). 4979–5001. 5 indexed citations
17.
Abdullah, A. Sheik, et al.. (2018). A Framework for Medical Big Data Processing: An Art of Survey. 63–69. 1 indexed citations
18.
Abdullah, A. Sheik, S. Selvakumar, P. Karthikeyan, & Murali Venkatesh. (2017). Comparing the Efficacy of Decision Tree and itsVariants using Medical Data. Indian Journal of Science and Technology. 10(18). 1–8. 11 indexed citations
19.
Suganya, R., et al.. (2017). Prediction of heart diseases using hybrid feature selection and modified Laplacian pyramid non-linear diffusion with soft computing methods. International Journal of Biomedical Engineering and Technology. 25(1). 30–30. 1 indexed citations
20.
Abdullah, A. Sheik, et al.. (2012). RANDOMIZED CLINICAL TRIAL OF SINGLE VERSUS THREE DOSES OF CEFAZOLIN AS PROPHYLAXIS FOR NONPERFORATED ACUTE APPENDICITIS. International Journal of Current Research and Review. 4(23). 124–130. 3 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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