Prableen Kaur

760 total citations
9 papers, 474 citations indexed

About

Prableen Kaur is a scholar working on Health Information Management, Management Information Systems and Artificial Intelligence. According to data from OpenAlex, Prableen Kaur has authored 9 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Health Information Management, 2 papers in Management Information Systems and 2 papers in Artificial Intelligence. Recurrent topics in Prableen Kaur's work include Artificial Intelligence in Healthcare (4 papers), Big Data and Business Intelligence (2 papers) and Machine Learning in Bioinformatics (1 paper). Prableen Kaur is often cited by papers focused on Artificial Intelligence in Healthcare (4 papers), Big Data and Business Intelligence (2 papers) and Machine Learning in Bioinformatics (1 paper). Prableen Kaur collaborates with scholars based in India and United States. Prableen Kaur's co-authors include Manik Sharma, Mamta Mittal, Ritu Gautam, Andrew B. Reinmann and Samriti Sharma and has published in prestigious journals such as Archives of Computational Methods in Engineering, Journal of Medical Systems and Frontiers in Forests and Global Change.

In The Last Decade

Prableen Kaur

9 papers receiving 435 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Prableen Kaur India	5	227	84	56	55	52	9	474
Adel Assiri Saudi Arabia	10	358 1.6×	96 1.1×	39 0.7×	46 0.8×	53 1.0×	19	537
Sapiah Sakri Saudi Arabia	7	205 0.9×	75 0.9×	59 1.1×	30 0.5×	54 1.0×	16	374
Shiva Shankar Reddy India	12	136 0.6×	73 0.9×	80 1.4×	45 0.8×	43 0.8×	86	478
Ramalingaswamy Cheruku India	16	292 1.3×	121 1.4×	73 1.3×	130 2.4×	52 1.0×	54	617
Jesús Maillo Spain	8	325 1.4×	47 0.6×	81 1.4×	38 0.7×	100 1.9×	10	561
Adriana Albu Romania	10	155 0.7×	50 0.6×	42 0.8×	28 0.5×	25 0.5×	47	454
Baijnath Kaushik India	13	245 1.1×	49 0.6×	87 1.6×	170 3.1×	114 2.2×	57	648
Shakeel Ahmed Saudi Arabia	14	150 0.7×	54 0.6×	64 1.1×	109 2.0×	86 1.7×	60	605
Georgios Kostopoulos Greece	14	254 1.1×	58 0.7×	44 0.8×	64 1.2×	72 1.4×	23	573
Nadim Obeid Jordan	14	400 1.8×	64 0.8×	87 1.6×	51 0.9×	182 3.5×	61	651

Countries citing papers authored by Prableen Kaur

Since Specialization

Citations

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

Fields of papers citing papers by Prableen Kaur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prableen Kaur

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

All Works

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9 of 9 papers shown

1.

Sharma, Manik, Prableen Kaur, & Samriti Sharma. (2024). Metaverse Unveiled: A Comprehensive Analysis of Taxonomy, Applications, and Future Opportunities. Archives of Computational Methods in Engineering. 32(4). 2255–2277. 1 indexed citations

2.

Kaur, Prableen & Manik Sharma. (2023). A NOVEL AND HYBRID WHALE OPTIMIZATION WITH RESTRICTED CROSSOVER AND MUTATION BASED FEATURE SELECTION METHOD FOR ANXIETY AND DEPRESSION. Psychiatria Danubina. 35(3). 355–368. 2 indexed citations

3.

Reinmann, Andrew B., et al.. (2023). Compensatory responses of leaf physiology reduce effects of spring frost defoliation on temperate forest tree carbon uptake. Frontiers in Forests and Global Change. 6. 2 indexed citations

4.

Kaur, Prableen. (2021). Big Data Analytics in Healthcare: A Review. Open MIND. 10(6). 1 indexed citations

5.

Sharma, Manik & Prableen Kaur. (2020). A Comprehensive Analysis of Nature-Inspired Meta-Heuristic Techniques for Feature Selection Problem. Archives of Computational Methods in Engineering. 28(3). 1103–1127. 209 indexed citations

6.

Gautam, Ritu, Prableen Kaur, & Manik Sharma. (2019). A comprehensive review on nature inspired computing algorithms for the diagnosis of chronic disorders in human beings. Progress in Artificial Intelligence. 8(4). 401–424. 41 indexed citations

7.

Kaur, Prableen & Manik Sharma. (2019). Diagnosis of Human Psychological Disorders using Supervised Learning and Nature-Inspired Computing Techniques: A Meta-Analysis. Journal of Medical Systems. 43(7). 204–204. 74 indexed citations

8.

Kaur, Prableen, Manik Sharma, & Mamta Mittal. (2018). Big Data and Machine Learning Based Secure Healthcare Framework. Procedia Computer Science. 132. 1049–1059. 129 indexed citations

9.

Kaur, Prableen & Manik Sharma. (2017). A Survey on Using Nature Inspired Computing for Fatal Disease Diagnosis. International Journal of Information System Modeling and Design. 8(2). 70–91. 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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