Kamalesh Chakravarty

837 total citations
50 papers, 563 citations indexed

About

Kamalesh Chakravarty is a scholar working on Neurology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Kamalesh Chakravarty has authored 50 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Neurology, 11 papers in Molecular Biology and 9 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Kamalesh Chakravarty's work include Epilepsy research and treatment (6 papers), S100 Proteins and Annexins (5 papers) and Cerebral Venous Sinus Thrombosis (5 papers). Kamalesh Chakravarty is often cited by papers focused on Epilepsy research and treatment (6 papers), S100 Proteins and Annexins (5 papers) and Cerebral Venous Sinus Thrombosis (5 papers). Kamalesh Chakravarty collaborates with scholars based in India, Canada and Taiwan. Kamalesh Chakravarty's co-authors include Pradeep Kumar, Shubham Misra, Amit Kumar, Kameshwar Prasad, Awadh Kishor Pandit, Abhishek Pathak, Vijaya Nath Mishra, Rahul Mishra, Deepika Joshi and Rameshwar Nath Chaurasia and has published in prestigious journals such as SHILAP Revista de lepidopterología, British Journal of Anaesthesia and Brain Behavior and Immunity.

In The Last Decade

Kamalesh Chakravarty

40 papers receiving 538 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kamalesh Chakravarty India 15 196 107 99 89 86 50 563
Sangam Kanekar United States 15 218 1.1× 174 1.6× 81 0.8× 87 1.0× 77 0.9× 68 755
Duško Kozić Serbia 14 146 0.7× 65 0.6× 61 0.6× 93 1.0× 45 0.5× 79 628
Mansour Mathkour United States 12 253 1.3× 156 1.5× 77 0.8× 64 0.7× 53 0.6× 79 549
Puneet Belani United States 13 263 1.3× 40 0.4× 193 1.9× 61 0.7× 59 0.7× 34 539
Larissa Hauer Austria 18 337 1.7× 38 0.4× 104 1.1× 201 2.3× 91 1.1× 29 850
Talan Zhang United States 16 164 0.8× 145 1.4× 70 0.7× 364 4.1× 71 0.8× 56 848
Valentina Citton Italy 13 192 1.0× 84 0.8× 92 0.9× 143 1.6× 65 0.8× 34 718
Zoltán Bajkó Romania 14 182 0.9× 38 0.4× 32 0.3× 83 0.9× 95 1.1× 68 592
Tolga Köroğlu Türkiye 14 81 0.4× 108 1.0× 71 0.7× 138 1.6× 155 1.8× 25 894
Panagiotis Kokotis Greece 16 389 2.0× 97 0.9× 56 0.6× 64 0.7× 20 0.2× 66 753

Countries citing papers authored by Kamalesh Chakravarty

Since Specialization
Citations

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

Fields of papers citing papers by Kamalesh Chakravarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kamalesh Chakravarty

This figure shows the co-authorship network connecting the top 25 collaborators of Kamalesh Chakravarty. A scholar is included among the top collaborators of Kamalesh Chakravarty 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 Kamalesh Chakravarty. Kamalesh Chakravarty 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, Pradeep, et al.. (2025). Relationship of apolipoprotein A and B level with the risk of stroke: A systematic review and meta-analysis. Atherosclerosis. 407. 119905–119905.
2.
3.
Sharma, Vaishali, et al.. (2025). Psychiatric symptoms and quality of life in patients with Idiopathic Intracranial Hypertension- A cross-sectional study. Journal of Clinical Neuroscience. 143. 111730–111730.
4.
Kumar, Ashok, Vaishali Sharma, P Kharbanda, et al.. (2024). Effectiveness of CBT for reducing depression and anxiety in people with epilepsy: A systematic review and meta-analysis of randomized controlled trials. Epilepsy & Behavior. 151. 109608–109608. 2 indexed citations
5.
Joshi, Deepika, Varun Kumar Singh, Abhishek Pathak, et al.. (2023). Thrombotic and Thromboembolic Complications After Vaccination Against COVID-19: A Systematic Review. Cureus. 15(4). e37275–e37275. 5 indexed citations
6.
Chakravarty, Kamalesh, et al.. (2023). Effect of persistent organic pollutants in patients with ischemic stroke and all stroke: A systematic review and meta-analysis. Toxicology. 494. 153567–153567. 5 indexed citations
7.
Sharma, Vaishali, et al.. (2021). Evaluation of prevalence and severity of obstructive sleep apnea using overnight - polysomnography in patients with idiopathic intracranial hypertension. Journal of the Neurological Sciences. 429. 119284–119284. 1 indexed citations
8.
Chakravarty, Kamalesh, et al.. (2021). Knowledge, attitude, and barriers for epilepsy surgery: A survey among resident doctors in a tertiary care center in India. Epilepsy & Behavior. 123. 108280–108280.
9.
Chakravarty, Kamalesh, et al.. (2021). Temporal lobe epilepsy with amygdala enlargement: A systematic review. Acta Neurologica Scandinavica. 144(3). 236–250. 14 indexed citations
10.
Ray, Sucharita, Kamalesh Chakravarty, Amit Rawat, et al.. (2020). Seronegative panencephalitis complicated by viral encephalomyelitis in a case of Good’s syndrome – a neuropathological report. International Journal of Neuroscience. 132(10). 1031–1036. 2 indexed citations
11.
Chaurasia, Rameshwar Nath, Kamalesh Chakravarty, Rahul Mishra, et al.. (2020). Neurological manifestations of COVID-19: a systematic review and meta-analysis of proportions. Neurological Sciences. 41(12). 3437–3470. 139 indexed citations
12.
Chakravarty, Kamalesh, et al.. (2020). Systemic lupus erythematosus with autoimmune neurological manifestations in a carrier of chronic granulomatous disease - a rare presentation. Journal of Neuroimmunology. 343. 577229–577229. 4 indexed citations
13.
Ray, Santanu, et al.. (2019). Neurological manifestations of dengue fever. Journal of the Neurological Sciences. 405. 33–34.
14.
Mehta, Sahil, et al.. (2019). Progressive dystonia as a presenting manifestation of GM1 gangliosidosis. Clinical Parkinsonism & Related Disorders. 1. 88–90. 1 indexed citations
15.
16.
Kumar, Amit, Shubham Misra, Pradeep Kumar, et al.. (2017). Association between endothelial nitric oxide synthase gene polymorphisms and risk of ischemic stroke: A meta-analysis. Neurology India. 65(1). 22–22. 14 indexed citations
17.
Kumar, Amit, Shubham Misra, Pradeep Kumar, et al.. (2016). Association between methylenetetrahydrofolate reductase (MTHFR) C677T gene polymorphism and risk of ischemic stroke in North Indian population: A hospital based case–control study. Egyptian Journal of Medical Human Genetics. 17(4). 359–365. 6 indexed citations
18.
Kumar, Amit, et al.. (2016). Genetics of ischemic stroke: An Indian scenario. Neurology India. 64(1). 29–29. 8 indexed citations
19.
Kumar, Amit, Pradeep Kumar, Manya Prasad, et al.. (2016). Association between Apolipoprotein ε4 Gene Polymorphism and Risk of Ischemic Stroke: A Meta-Analysis. Annals of Neurosciences. 23(2). 113–121. 21 indexed citations
20.
Misra, Shubham, Pradeep Kumar, Amit Kumar, et al.. (2016). Genetic association between inflammatory genes (IL-1α, CD14, LGALS2, PSMA6) and risk of ischemic stroke: A meta-analysis. Meta Gene. 8. 21–29. 15 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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