Atul Kumar

540 total citations
23 papers, 281 citations indexed

About

Atul Kumar is a scholar working on Physiology, Health Information Management and Artificial Intelligence. According to data from OpenAlex, Atul Kumar has authored 23 papers receiving a total of 281 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Physiology, 5 papers in Health Information Management and 5 papers in Artificial Intelligence. Recurrent topics in Atul Kumar's work include Alzheimer's disease research and treatments (7 papers), Dementia and Cognitive Impairment Research (5 papers) and Artificial Intelligence in Healthcare (5 papers). Atul Kumar is often cited by papers focused on Alzheimer's disease research and treatments (7 papers), Dementia and Cognitive Impairment Research (5 papers) and Artificial Intelligence in Healthcare (5 papers). Atul Kumar collaborates with scholars based in Sweden, India and United States. Atul Kumar's co-authors include Sachidanand Singh, Oskar Hansson, Niklas Mattsson, K. Panneerselvam, Erik Stomrud, Sebastian Palmqvist, D. Jeya Sundara Sharmila, Shorena Janelidze, Olof Strandberg and Divya Bali and has published in prestigious journals such as Nature Neuroscience, Neurology and Scientific Reports.

In The Last Decade

Atul Kumar

22 papers receiving 264 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Atul Kumar Sweden 10 82 70 53 53 39 23 281
Erfan Younesi Germany 14 121 1.5× 365 5.2× 18 0.3× 131 2.5× 58 1.5× 35 643
Xinzhong Li United Kingdom 11 146 1.8× 219 3.1× 20 0.4× 25 0.5× 41 1.1× 18 507
Yishen Chen China 11 103 1.3× 123 1.8× 24 0.5× 24 0.5× 7 0.2× 22 376
Alzheimer’s Disease Neuroimaging Initiative China 13 133 1.6× 83 1.2× 36 0.7× 72 1.4× 151 3.9× 35 436
Renjie Li Australia 10 39 0.5× 30 0.4× 8 0.2× 80 1.5× 77 2.0× 39 364
Shantanu Ghosh India 7 131 1.6× 36 0.5× 20 0.4× 40 0.8× 12 0.3× 15 374
Josefa Díaz‐Álvarez Spain 10 31 0.4× 25 0.4× 13 0.2× 69 1.3× 65 1.7× 23 242
Lilia Mesrob France 7 110 1.3× 106 1.5× 37 0.7× 63 1.2× 175 4.5× 7 524
R. Prashanth India 8 180 2.2× 35 0.5× 28 0.5× 50 0.9× 8 0.2× 15 474

Countries citing papers authored by Atul Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Atul Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Atul Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Atul Kumar. A scholar is included among the top collaborators of Atul Kumar 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 Atul Kumar. Atul Kumar 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.
Kumar, Atul & Rupesh Kumar Dewang. (2025). Comprehensive insights into healthcare IoT: the role of machine learning and deep learning approaches. Multimedia Tools and Applications. 84(34). 42215–42256.
2.
Gomes, Bárbara Fernandes, Atul Kumar, Nicholas J. Ashton, et al.. (2024). Corticotropin-releasing hormone as a candidate biomarker for parkinsonian disorders. Brain Communications. 6(6). fcae414–fcae414. 3 indexed citations
3.
Binette, Alexa Pichet, Chris Gaiteri, Malin Wennström, et al.. (2024). Proteomic changes in Alzheimer’s disease associated with progressive Aβ plaque and tau tangle pathologies. Nature Neuroscience. 27(10). 1880–1891. 40 indexed citations
4.
Insel, Philip S., et al.. (2023). Genetic Moderation of the Association of β-Amyloid With Cognition and MRI Brain Structure in Alzheimer Disease. Neurology. 101(1). e20–e29. 1 indexed citations
5.
Pereira, Joana B., Atul Kumar, Sara Hall, et al.. (2023). DOPA decarboxylase is an emerging biomarker for Parkinsonian disorders including preclinical Lewy body disease. Nature Aging. 3(10). 1201–1209. 38 indexed citations
6.
Hristovska, Inès, Atul Kumar, Alexa Pichet Binette, et al.. (2023). Identification of Distinct and Shared Biomarkers in Cerebral Small Vessel Disease (SVD) through Proteomic Profiling of Cerebrospinal Fluid. Alzheimer s & Dementia. 19(S24). 1 indexed citations
7.
Kumar, Atul, Katarina Nägga, Gunnar Engström, et al.. (2023). Polygenic risk of type 2 diabetes is associated with incident vascular dementia: a prospective cohort study. Brain Communications. 5(2). fcad054–fcad054. 10 indexed citations
8.
Kumar, Atul, Shorena Janelidze, Erik Stomrud, et al.. (2022). β-Amyloid–Dependent and –Independent Genetic Pathways Regulating CSF Tau Biomarkers in Alzheimer Disease. Neurology. 99(5). e476–e487. 5 indexed citations
9.
Hansson, Oskar, Atul Kumar, Shorena Janelidze, et al.. (2022). The genetic regulation of protein expression in cerebrospinal fluid. EMBO Molecular Medicine. 15(1). e16359–e16359. 19 indexed citations
10.
Kumar, Atul, Maryam Shoai, Sebastian Palmqvist, et al.. (2021). Genetic effects on longitudinal cognitive decline during the early stages of Alzheimer’s disease. Scientific Reports. 11(1). 19853–19853. 9 indexed citations
11.
Franzmeier, Nicolai, Rik Ossenkoppele, Matthias Brendel, et al.. (2021). The BIN1 rs744373 Alzheimer’s disease risk SNP is associated with faster Aβ‐associated tau accumulation and cognitive decline. Alzheimer s & Dementia. 17(S1). 3 indexed citations
12.
Sinha, Anurag & Atul Kumar. (2020). Wine Quality and Taste Classification Using Machine Learning Model. 4(4). 715–721. 7 indexed citations
13.
Arulmozhi, S., et al.. (2018). An insight into anti-arthritic property OF C25H34O7 for Rheumatoid arthritis using molecular modelling and molecular dynamics approach. Informatics in Medicine Unlocked. 16. 100145–100145. 3 indexed citations
14.
Kumar, Atul, D. Jeya Sundara Sharmila, & Sachidanand Singh. (2017). SVMRFE based approach for prediction of most discriminatory gene target for type II diabetes. Genomics Data. 12. 28–37. 16 indexed citations
15.
Kumar, Atul & D. Jeya Sundara Sharmila. (2015). Algorithmic Approach for Removing the Redundancy in Diabetic Gene Categories Based on Semantic Similarity and Gene Expression Data. Interdisciplinary Sciences Computational Life Sciences. 8(2). 162–168. 3 indexed citations
16.
Kumar, Atul. (2013). Diagnosis of heart disease using Advanced Fuzzy resolution Mechanism. 19 indexed citations
17.
Kumar, Atul. (2013). Generating Rules for Advanced Fuzzy Resolution Mechanism to Diagnosis Heart Disease. 77(11). 6–12. 4 indexed citations
18.
Agarwal, Ankur, et al.. (2012). MULTI AGENT BASED APPROACH FOR NETWORK INTRUSION DETECTION USING DATA MINING CONCEPT. Journal of Global Research in Computer Sciences. 3(3). 29–32. 1 indexed citations
19.
Kumar, Atul, et al.. (2011). Fuzzy Expert System for Diabetes using Fuzzy Verdict Mechanism. 22 indexed citations
20.
Singh, Sachidanand, et al.. (2010). Diagnosis of Arthritis Through Fuzzy Inference System. Journal of Medical Systems. 36(3). 1459–1468. 42 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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