Subrato Bharati

1.9k total citations
43 papers, 887 citations indexed

About

Subrato Bharati is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Subrato Bharati has authored 43 papers receiving a total of 887 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 20 papers in Artificial Intelligence and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Subrato Bharati's work include COVID-19 diagnosis using AI (17 papers), AI in cancer detection (11 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Subrato Bharati is often cited by papers focused on COVID-19 diagnosis using AI (17 papers), AI in cancer detection (11 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Subrato Bharati collaborates with scholars based in Bangladesh, Canada and United States. Subrato Bharati's co-authors include Prajoy Podder, M. Rubaiyat Hossain Mondal, V. B. Surya Prasath, Mohammad Atikur Rahman, Utku Köse, Md Junayed Hasan, Dang N. H. Thanh, Farzin Piltan, Aditya Khamparia and Joarder Kamruzzaman and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Sensors.

In The Last Decade

Subrato Bharati

41 papers receiving 827 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subrato Bharati Bangladesh 17 411 290 122 99 80 43 887
M. Rubaiyat Hossain Mondal Bangladesh 18 518 1.3× 304 1.0× 121 1.0× 109 1.1× 86 1.1× 75 1.2k
Manal Alghamdi Saudi Arabia 19 471 1.1× 279 1.0× 19 0.2× 63 0.6× 128 1.6× 44 1.1k
Samrat Kumar Dey Bangladesh 17 467 1.1× 272 0.9× 37 0.3× 126 1.3× 173 2.2× 51 1.0k
Taye Girma Debelee Ethiopia 17 417 1.0× 268 0.9× 17 0.1× 53 0.5× 95 1.2× 34 963
Amirata Ghorbani United States 8 567 1.4× 486 1.7× 177 1.5× 21 0.2× 64 0.8× 15 1.4k
Ruidi Chen United States 7 515 1.3× 64 0.2× 67 0.5× 63 0.6× 36 0.5× 18 732
Jawad Rasheed Türkiye 15 315 0.8× 247 0.9× 40 0.3× 59 0.6× 155 1.9× 71 780
Ahmed T. Sahlol Egypt 11 599 1.5× 501 1.7× 63 0.5× 41 0.4× 50 0.6× 20 1.0k
Shiva Toumaj Iran 7 193 0.5× 149 0.5× 57 0.5× 84 0.8× 52 0.7× 11 511
Vaishali India 7 295 0.7× 393 1.4× 79 0.6× 43 0.4× 24 0.3× 43 603

Countries citing papers authored by Subrato Bharati

Since Specialization
Citations

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

Fields of papers citing papers by Subrato Bharati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subrato Bharati

This figure shows the co-authorship network connecting the top 25 collaborators of Subrato Bharati. A scholar is included among the top collaborators of Subrato Bharati 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 Subrato Bharati. Subrato Bharati 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.
Bharati, Subrato, M. Omair Ahmad, & M.N.S. Swamy. (2024). MedSegNet: A Lightweight Convolutional Network Combining Dual Self-Attention and Multi-Scale Attention for Medical Image Segmentation. 965–969. 1 indexed citations
2.
3.
Bharati, Subrato, M. Omair Ahmad, & M. N. S. Swamy. (2024). MAGNet: A Convolutional Neural Network with Multi-Scale and Global Attention Modules for Medical Image Segmentation. 1–5. 2 indexed citations
4.
Podder, Prajoy, et al.. (2023). Rethinking Densely Connected Convolutional Networks for Diagnosing Infectious Diseases. Computers. 12(5). 95–95. 14 indexed citations
5.
Podder, Prajoy, et al.. (2023). LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases. Sensors. 23(1). 480–480. 36 indexed citations
6.
Sekaran, Ramesh, et al.. (2022). Nonlinear Cosine Neighborhood Time Series‐Based Deep Learning for the Prediction and Analysis of COVID‐19 in India. Wireless Communications and Mobile Computing. 2022(1). 2 indexed citations
7.
Köse, Utku, V. B. Surya Prasath, M. Rubaiyat Hossain Mondal, Prajoy Podder, & Subrato Bharati. (2022). Artificial Intelligence and Smart Agriculture Technology. Auerbach Publications eBooks. 7 indexed citations
8.
Bharati, Subrato, Prajoy Podder, M. Rubaiyat Hossain Mondal, & V. B. Surya Prasath. (2021). CO-ResNet: Optimized ResNet model for COVID-19 diagnosis from X-ray images. International Journal of Hybrid Intelligent Systems. 17(1-2). 71–85. 59 indexed citations
9.
Bharati, Subrato. (2021). BUSINESS INTELLIGENCE AND INDUSTRY 5.0. Journal of the International Academy of Case Studies. 27. 1–3. 2 indexed citations
10.
Bharati, Subrato, Prajoy Podder, M. Rubaiyat Hossain Mondal, & V. B. Surya Prasath. (2021). Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive Review. arXiv (Cornell University). 13. 91–112. 1 indexed citations
11.
Mondal, M. Rubaiyat Hossain, Subrato Bharati, & Prajoy Podder. (2021). CO-IRv2: Optimized InceptionResNetV2 for COVID-19 detection from chest CT images. PLoS ONE. 16(10). e0259179–e0259179. 43 indexed citations
12.
Bharati, Subrato, Prajoy Podder, M. Rubaiyat Hossain Mondal, & V. B. Surya Prasath. (2021). Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive Review. arXiv (Cornell University). 27 indexed citations
13.
Bharati, Subrato. (2020). HOW ARTIFICIAL INTELLIGENCE IMPACTS BUSINESSES IN THE PERIOD OF PANDEMICS. Journal of the International Academy of Case Studies. 26(5). 1–2. 3 indexed citations
14.
Bharati, Subrato & Prajoy Podder. (2020). Disease Detection from Lung X-ray Images based on Hybrid Deep Learning. arXiv (Cornell University). 2 indexed citations
15.
Podder, Prajoy, et al.. (2020). Review on the Security Threats of Internet of Things. International Journal of Computer Applications. 176(41). 37–45. 20 indexed citations
16.
Bharati, Subrato, et al.. (2019). Lung cancer recognition and prediction according to random forest ensemble and RUSBoost algorithm using LIDC data. International Journal of Hybrid Intelligent Systems. 15(2). 91–100. 11 indexed citations
17.
Bharati, Subrato, Mohammad Atikur Rahman, Sanjoy Mandal, & Prajoy Podder. (2018). Analysis of DWT, DCT, BFO & PBFO Algorithm for the Purpose of Medical Image Watermarking. 1–6. 10 indexed citations
18.
Bharati, Subrato, Mohammad Atikur Rahman, & Prajoy Podder. (2018). Breast Cancer Prediction Applying Different Classification Algorithm with Comparative Analysis using WEKA. 581–584. 35 indexed citations
19.
Bharati, Subrato, et al.. (2018). EEG Eye State Prediction and Classification in order to Investigate Human Cognitive State. 1–4. 3 indexed citations
20.

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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