Sujit Kumar Das

831 total citations
34 papers, 470 citations indexed

About

Sujit Kumar Das is a scholar working on Artificial Intelligence, Endocrinology, Diabetes and Metabolism and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Sujit Kumar Das has authored 34 papers receiving a total of 470 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 9 papers in Endocrinology, Diabetes and Metabolism and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Sujit Kumar Das's work include Diabetic Foot Ulcer Assessment and Management (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and AI in cancer detection (6 papers). Sujit Kumar Das is often cited by papers focused on Diabetic Foot Ulcer Assessment and Management (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and AI in cancer detection (6 papers). Sujit Kumar Das collaborates with scholars based in India, Lebanon and Australia. Sujit Kumar Das's co-authors include Pinki Roy, Arnab Kumar Mishra, Sivaji Bandyopadhyay, Pranav Kumar Singh, Suyel Namasudra, Tapas K. Chaudhuri, Monojit Debnath, Nageswara Rao Moparthi, Arun Kumar Sangaiah and Anshuman Kalla and has published in prestigious journals such as SHILAP Revista de lepidopterología, Image and Vision Computing and The Canadian Journal of Psychiatry.

In The Last Decade

Sujit Kumar Das

30 papers receiving 450 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sujit Kumar Das India 13 196 187 113 86 53 34 470
Arnab Kumar Mishra India 9 183 0.9× 181 1.0× 86 0.8× 97 1.1× 44 0.8× 14 430
Audrey Huong Malaysia 9 55 0.3× 109 0.6× 38 0.3× 12 0.1× 18 0.3× 64 278
Maali Alabdulhafith Saudi Arabia 10 117 0.6× 45 0.2× 12 0.1× 81 0.9× 6 0.1× 37 325
Hassan Douzi Morocco 10 31 0.2× 22 0.1× 50 0.4× 99 1.2× 32 0.6× 39 261
Jaber Alyami Saudi Arabia 11 160 0.8× 161 0.9× 25 0.2× 61 0.7× 38 390
Maria João M. Vasconcelos Portugal 11 118 0.6× 31 0.2× 8 0.1× 119 1.4× 5 0.1× 41 335
Junaid Asghar Pakistan 9 164 0.8× 83 0.4× 7 0.1× 21 0.2× 3 0.1× 16 373
Virginie Felizardo Portugal 9 48 0.2× 23 0.1× 64 0.6× 37 0.4× 5 0.1× 23 263
Puneet Goyal India 11 37 0.2× 12 0.1× 11 0.1× 124 1.4× 29 0.5× 53 280

Countries citing papers authored by Sujit Kumar Das

Since Specialization
Citations

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

Fields of papers citing papers by Sujit Kumar Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sujit Kumar Das. 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 Sujit Kumar Das. The network helps show where Sujit Kumar Das may publish in the future.

Co-authorship network of co-authors of Sujit Kumar Das

This figure shows the co-authorship network connecting the top 25 collaborators of Sujit Kumar Das. A scholar is included among the top collaborators of Sujit Kumar Das 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 Sujit Kumar Das. Sujit Kumar Das 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.
Sarkar, Partha, et al.. (2025). Edible bamboo shoots: a sustainable nexus of nutrition, livelihood, and food security for rural communities in India. Frontiers in Nutrition. 12. 1654510–1654510.
2.
Das, Sujit Kumar, et al.. (2025). Assessing microplastic accumulation in the hepatopancreas of marine and freshwater crabs from the North-East Part of the Bay of Bengal. Environmental Research Communications. 7(8). 85001–85001.
3.
Das, Sujit Kumar, et al.. (2024). A Smart Healthcare System Using Consumer Electronics and Federated Learning to Automatically Diagnose Diabetic Foot Ulcers.. International Journal of Interactive Multimedia and Artificial Intelligence. 9(2). 5–17. 1 indexed citations
4.
Das, Sujit Kumar, et al.. (2023). AESPNet: Attention Enhanced Stacked Parallel Network to improve automatic Diabetic Foot Ulcer identification. Image and Vision Computing. 138. 104809–104809. 12 indexed citations
5.
Das, Sujit Kumar, Pinki Roy, Prabhishek Singh, et al.. (2023). Diabetic Foot Ulcer Identification: A Review. Diagnostics. 13(12). 1998–1998. 20 indexed citations
6.
Das, Sujit Kumar, et al.. (2023). Attention Based CNN to Improve Identification of Ischaemia and Infection in DFU. 1–7. 2 indexed citations
7.
Singh, Pranav Kumar, et al.. (2023). SE_SPnet: Rice leaf disease prediction using stacked parallel convolutional neural network with squeeze‐and‐excitation. Expert Systems. 40(7). 13 indexed citations
8.
Mishra, Arnab Kumar, Pinki Roy, Sivaji Bandyopadhyay, & Sujit Kumar Das. (2022). A multi‐task learning based approach for efficient breast cancer detection and classification. Expert Systems. 39(9). 6 indexed citations
9.
Das, Sujit Kumar, Pinki Roy, & Arnab Kumar Mishra. (2021). Recognition of ischaemia and infection in diabetic foot ulcer: A deep convolutional neural network based approach. International Journal of Imaging Systems and Technology. 32(1). 192–208. 27 indexed citations
10.
Das, Sujit Kumar, Pinki Roy, & Arnab Kumar Mishra. (2021). DFU_SPNet: A stacked parallel convolution layers based CNN to improve Diabetic Foot Ulcer classification. ICT Express. 8(2). 271–275. 57 indexed citations
11.
Das, Sujit Kumar, et al.. (2021). Application of Transformer-Based Language Models to Detect Hate Speech in Social Media. 2(4). 278–286. 14 indexed citations
12.
Das, Sujit Kumar, Sukanta Kumar Pradhan, Kailash Chandra Samal, & Nihar Ranjan Singh. (2021). Structural, functional, and evolutionary analysis of Cry toxins of Bacillus thuringiensis: an in silico study. Egyptian Journal of Biological Pest Control. 31(1). 7 indexed citations
13.
Mishra, Arnab Kumar, Sujit Kumar Das, Pinki Roy, & Sivaji Bandyopadhyay. (2020). Identifying COVID19 from Chest CT Images: A Deep Convolutional Neural Networks Based Approach. Journal of Healthcare Engineering. 2020. 1–7. 107 indexed citations
14.
Das, Sujit Kumar, Arnab Kumar Mishra, & Pinki Roy. (2019). Automatic Diabetes Prediction Using Tree Based Ensemble Learners. SSRN Electronic Journal. 13 indexed citations
15.
Das, Sujit Kumar, Snehasish Mishra, R.K. Swain, et al.. (2016). INCIDENCE OF INFERTILITY AND BIOCHEMICAL PROFILE OF CROSSBRED COWS IN CUTTACK DISTRICT OF ODISHA, INDIA. SHILAP Revista de lepidopterología. 2 indexed citations
16.
Das, Sujit Kumar, et al.. (2014). Detecting and Punishing the Selfish Node and its Behavior in WSN. 6(1). 11–15.
17.
18.
Das, Sujit Kumar, et al.. (2009). PLASMA HOMOVANILLIC ACID IN DELUSIONAL DISORDER : IMPLICATIONS FOR DOPAMINE DYSFUNCTION. International Journal of Chemical Sciences. 7(3). 1583–1590. 1 indexed citations
19.
Debnath, Monojit, et al.. (2005). Study of HLA-Linked Genes in Paranoid Schizophrenia in an Indian Bengalee Population. International Journal of Human Genetics. 5(4). 273–277. 5 indexed citations
20.
Debnath, Monojit, et al.. (2000). Role of hla class-I antigens in delusional disorder.. PubMed. 42(3). 275–9. 1 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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