Preesat Biswas

514 total citations · 1 hit paper
16 papers, 328 citations indexed

About

Preesat Biswas is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Preesat Biswas has authored 16 papers receiving a total of 328 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Preesat Biswas's work include COVID-19 diagnosis using AI (3 papers), Spectroscopy and Chemometric Analyses (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Preesat Biswas is often cited by papers focused on COVID-19 diagnosis using AI (3 papers), Spectroscopy and Chemometric Analyses (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Preesat Biswas collaborates with scholars based in India, Bangladesh and Thailand. Preesat Biswas's co-authors include Santi Kumari Behera, Prabira Kumar Sethy, Adnan Mannan, Farhana Akter, Aziz Nanthaamornphong, Asish Kumar Ghosh, S. Shanthi and Nalini Kanta Barpanda and has published in prestigious journals such as Diagnostic Microbiology and Infectious Disease, New Microbes and New Infections and Współczesna Onkologia.

In The Last Decade

Preesat Biswas

10 papers receiving 310 citations

Hit Papers

Detection of coronavirus Disease (COVID-19) based on Deep... 2020 2026 2022 2024 2020 50 100 150 200 250
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.

  1. Detection of coronavirus Disease (COVID-19) based on Deep Features and Support Vector Machine
    2020 262 citations Prabira Kumar Sethy, Santi Kumari Behera et al. International Journal of Mathematical Engineering and Management Sciences profile →

Peers

Preesat Biswas
Yunan Wu United States
Tasmi Tamanna Australia
Satyabhuwan Singh Netam India
Jin Uk Heo United States
Vruddhi Shah India
Khalid El Asnaoui Portugal
Youness Chawki Portugal
Ziwang Huang China
Aysen Degerli Finland
Lucas Teixeira Brazil
Yunan Wu United States
Preesat Biswas
Citations per year, relative to Preesat Biswas Preesat Biswas (= 1×) peers Yunan Wu

Countries citing papers authored by Preesat Biswas

Since Specialization
Citations

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

Fields of papers citing papers by Preesat Biswas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Preesat Biswas

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

All Works

16 of 16 papers shown
1.
Biswas, Preesat, et al.. (2025). Evaluating saliva for SARS-CoV-2 detection: A practical alternative. Diagnostic Microbiology and Infectious Disease. 113(2). 116902–116902.
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Shanthi, S., et al.. (2024). Lipid droplet segmentation using U-net convolutional neural network architecture. AIP conference proceedings. 3122. 30021–30021.
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Sethy, Prabira Kumar, et al.. (2023). Evaluation of optimization techniques with support vector machine for identification of dry beans. Indonesian Journal of Electrical Engineering and Computer Science. 32(2). 704–704. 3 indexed citations
7.
Barpanda, Nalini Kanta, et al.. (2022). Adaptation issues of machine learning in safety digitization. Indonesian Journal of Electrical Engineering and Computer Science. 29(3). 1802–1802. 1 indexed citations
8.
Biswas, Preesat, et al.. (2022). Brain tumor magnetic resonance images classification based machine learning paradigms. Współczesna Onkologia. 26(4). 268–274. 13 indexed citations
9.
Mannan, Adnan, et al.. (2021). A multi-centre, cross-sectional study on coronavirus disease 2019 in Bangladesh: clinical epidemiology and short-term outcomes in recovered individuals. New Microbes and New Infections. 40. 100838–100838. 24 indexed citations
10.
Biswas, Preesat. (2021). A Simulational Performance of 5G MIMO Systems applying UFMC( Universal Filtered Multicarrier) Study. Türk bilgisayar ve matematik eğitimi dergisi. 12(2). 3176–3183.
11.
Sethy, Prabira Kumar, et al.. (2020). Detection of coronavirus Disease (COVID-19) based on Deep Features and Support Vector Machine. International Journal of Mathematical Engineering and Management Sciences. 5(4). 643–651. 262 indexed citations breakdown →
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Sethy, Prabira Kumar, et al.. (2020). Quality Evaluation of Pomegranate Fruit using Image Processing Techniques. 38–40. 6 indexed citations
15.
Biswas, Preesat, et al.. (2020). Minimum Time Delay and More Efficient Image Filtering Brain Tumour Detection with the help of MATLAB. 1. 1195–1199. 6 indexed citations
16.
Sethy, Prabira Kumar, et al.. (2020). Detection of Coronavirus Disease (COVID-19) Based on Deep Features and Support Vector Machine. 7 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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