Pradeep Kumar Das

66 papers receiving 4.5k citations

Pradeep Kumar Das's Hit Papers

An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images 2023 · 106 citations
1060+7+14Years since publication250500750

Peers

Pradeep Kumar Das
Comparison fields: 5 of 139
  • Aging 171
  • Plant Science 2.4k
  • Molecular Biology 2.8k
  • Computer Vision and Pattern Recognition 554
  • Biophysics 145
Replace Zhaolei Zhang with:
Zhaolei Zhang Canada
Beth A. Cimini United States
Julien Gagneur Germany
Leo J. Lee Canada
Dongxiao Zhu United States
Carolina Wählby Sweden
Robert A. Lindquist United States
Paul Bertone United States
David P. Kreil Austria
Carsten Marr Germany
Pradeep Kumar Das relative to Zhaolei Zhang Canada Zhaolei Zhang's profile →
Citations per field
00.5×6.7×
Zhaolei Zhang · 1×
Citations per year

Countries citing papers authored by Pradeep Kumar Das

Since Specialization
Citations

This map shows the geographic impact of Pradeep 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 Pradeep 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 Pradeep Kumar Das more than expected).

Fields of papers citing papers by Pradeep Kumar Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pradeep Kumar 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 Pradeep Kumar Das Line = papers co-authored together Pradeep Kumar Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Patterns of Auxin Transport and Gene Expression during Primordium Development Revealed by Live Imaging of the Arabidopsis Inflorescence Meristem
Hit paper breakdown →
2005957
2 1996429
3 2007317
4 2004263
5 2010224
6 2013161
7 2021133
8 2015129
9 1996129
10 2011129
11
An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images
Hit paper breakdown →
2023106
12 1998100
13 202296
14 202191
15 202285
16 199885
17 200981
18 201775
19 201967
20 202265

About Pradeep Kumar Das

Pradeep Kumar Das is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Plant Science, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 71 papers that have together received 4.6k indexed citations. Recurring topics across this work include Plant Molecular Biology Research (18 papers), Digital Imaging for Blood Diseases (16 papers), Plant Reproductive Biology (16 papers), COVID-19 diagnosis using AI (14 papers), AI in cancer detection (13 papers), TGF-β signaling in diseases (6 papers), Metal complexes synthesis and properties (5 papers) and Brain Tumor Detection and Classification (4 papers). The work is most often cited by research in Aging (171 citations), Plant Science (2.4k citations), Molecular Biology (2.8k citations), Computer Vision and Pattern Recognition (554 citations) and Biophysics (145 citations). Pradeep Kumar Das has collaborated with scholars based in India, United States and France. Frequent co-authors include Sukadev Meher, Elliot M. Meyerowitz, Marcus G. Heisler, Carolyn Ohno, G. Venugopala Reddy, Richard W. Padgett, Patrick Sieber, Jeff A. Long, Adyasha Sahu and Vincent Mirabet. Their work appears in journals such as Development, Engineering Applications of Artificial Intelligence, Proceedings of the National Academy of Sciences, Biomedical Signal Processing and Control and Journal of Applied Polymer Science.

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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