Subrata Bhattacharjee
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Neurology top 10%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Co-authors
- Heung‐Kook ChoiNuwan MadusankaHee‐Cheol KimNam-Hoon ChoWilliam L. GrosshandlerTagne Poupi Theodore ArmandAbdullahAli Hussain
- Topics
- AI in cancer detection (15 papers)Radiomics and Machine Learning in Medical Imaging (11 papers)Medical Imaging and Analysis (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaSensorsCombustion and Flame
- Partner nations
- South KoreaUnited StatesSri Lanka
In The Last Decade
Subrata Bhattacharjee
30 papers receiving 320 citations
Peers
Comparison fields: 5 of 90
- Artificial Intelligence 141
- Radiology, Nuclear Medicine and Imaging 121
- Neurology 81
- Computer Vision and Pattern Recognition 62
- Biomedical Engineering 35
Countries citing papers authored by Subrata Bhattacharjee
This map shows the geographic impact of Subrata Bhattacharjee'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 Subrata Bhattacharjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subrata Bhattacharjee more than expected).
Fields of papers citing papers by Subrata Bhattacharjee
This network shows the impact of papers produced by Subrata Bhattacharjee. 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 Subrata Bhattacharjee. The network helps show where Subrata Bhattacharjee may publish in the future.
Co-authorship network of co-authors of Subrata Bhattacharjee
This figure shows the co-authorship network connecting the top 25 collaborators of Subrata Bhattacharjee. A scholar is included among the top collaborators of Subrata Bhattacharjee 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 Subrata Bhattacharjee. Subrata Bhattacharjee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 7 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 14 | |
| 8 | 12 | |
| 9 | 9 | |
| 10 | 6 | |
| 11 | 4 | |
| 12 | 25 | |
| 13 | 3 | |
| 14 | Multichannel Convolution Neural Network Classification for the Detection of Histological Pattern in Prostate Biopsy Images | 1 |
| 15 | 5 | |
| 16 | A Study on Deep Learning Binary Classification of Prostate Pathological Images Using Multiple Image Enhancement Techniques | 2 |
| 17 | 1 | |
| 18 | 3 | |
| 19 | 0 | |
| 20 | 13 |
About Subrata Bhattacharjee
Subrata Bhattacharjee is a scholar working on Neurology, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 34 papers that have together received 336 indexed citations. Recurring topics across this work include AI in cancer detection (15 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Medical Imaging and Analysis (9 papers). The work is most often cited by research in Neurology (81 citations), Health Informatics (10 citations) and Radiology, Nuclear Medicine and Imaging (121 citations). Subrata Bhattacharjee has collaborated with scholars based in South Korea, United States and Sri Lanka. Frequent co-authors include Heung‐Kook Choi, Nuwan Madusanka, Hee‐Cheol Kim, Nam-Hoon Cho, William L. Grosshandler, Tagne Poupi Theodore Armand, Abdullah, Ali Hussain, Ali Athar and Sikandar Ali. Their work appears in journals such as SHILAP Revista de lepidopterología, Sensors and Combustion and Flame.
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.