Dipayan Das

20 papers receiving 436 citations

Peers

Dipayan Das
Comparison fields: 5 of 86
  • Health Informatics 53
  • Radiology, Nuclear Medicine and Imaging 224
  • Neurology 40
  • Artificial Intelligence 127
  • Health Information Management 16
Replace Shaoguo Cui with:
Shaoguo Cui China
Il Hyun Choi South Korea
Hongfeng Ma China
Yoshie Kodera Japan
Cong Fang China
Eduardo Costa da Silva Brazil
Gulistan Raja Pakistan
Thomas W. Rogers United Kingdom
Jizong Peng China
Dipayan Das relative to Shaoguo Cui China Shaoguo Cui's profile →
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Citations per year

Countries citing papers authored by Dipayan Das

Since Specialization
Citations

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

Fields of papers citing papers by Dipayan Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dipayan Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dipayan Das Line = papers co-authored together Dipayan Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020198
2 201293
3 202066
4 201526
5 202112
6 201210
7 20209
8 20106
9 20255
10 20164
11 20114
12 20113
13 20163
14 20222
15 20152
16 20221
17 20091
18 20251
19
Design of a Single Microcontroller based 29-Channel Data Logging System
20141
20 20101

About Dipayan Das

Dipayan Das is a scholar working on Electrical and Electronic Engineering, Aerospace Engineering, Control and Systems Engineering, Infectious Diseases and Media Technology, having authored 21 papers that have together received 448 indexed citations. Recurring topics across this work include CCD and CMOS Imaging Sensors (6 papers), Infrared Target Detection Methodologies (5 papers), COVID-19 diagnosis using AI (3 papers), Image Processing Techniques and Applications (3 papers), Robot Manipulation and Learning (3 papers), Tuberculosis Research and Epidemiology (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Muscle activation and electromyography studies (2 papers). The work is most often cited by research in Health Informatics (53 citations), Radiology, Nuclear Medicine and Imaging (224 citations), Neurology (40 citations), Artificial Intelligence (127 citations) and Health Information Management (16 citations). Dipayan Das has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include KC Santosh, Umapada Pal, Danial Chitnis, David R. S. Cumming, Timothy D. Drysdale, Steve Collins, Palash Ghosal, Debashis Nandi, Neha Upadhyay and Loïc Epelboin. Their work appears in journals such as Plasmonics, Clinical Microbiology and Infection, IEEE Transactions on Emerging Topics in Computing, Computer Methods and Programs in Biomedicine and Physical and Engineering Sciences in Medicine.

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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