Pankaj K. Jain

684 total citations
12 papers, 454 citations indexed

About

Pankaj K. Jain is a scholar working on Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Pankaj K. Jain has authored 12 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Pulmonary and Respiratory Medicine, 8 papers in Cardiology and Cardiovascular Medicine and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Pankaj K. Jain's work include Cerebrovascular and Carotid Artery Diseases (10 papers), Cardiovascular Health and Disease Prevention (8 papers) and Cardiac Imaging and Diagnostics (4 papers). Pankaj K. Jain is often cited by papers focused on Cerebrovascular and Carotid Artery Diseases (10 papers), Cardiovascular Health and Disease Prevention (8 papers) and Cardiac Imaging and Diagnostics (4 papers). Pankaj K. Jain collaborates with scholars based in India, Italy and United States. Pankaj K. Jain's co-authors include Jasjit S. Suri, Luca Saba, Neeraj Sharma, Andrew Nicolaides, John R. Laird, Tadashi Araki, Shoaib Shafique, Nobutaka Ikeda, A Giannopoulos and Amer M. Johri and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computer Methods and Programs in Biomedicine and Computers in Biology and Medicine.

In The Last Decade

Pankaj K. Jain

11 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
Pankaj K. Jain India 11 228 222 190 105 70 12 454
Tomaž Omerzu Slovenia 7 163 0.7× 204 0.9× 158 0.8× 80 0.8× 63 0.9× 9 429
Sumit K. Banchhor India 12 219 1.0× 206 0.9× 186 1.0× 79 0.8× 58 0.8× 19 395
Ran Zhou China 11 221 1.0× 124 0.6× 314 1.7× 31 0.3× 52 0.7× 44 564
Ian Chan Canada 11 203 0.9× 362 1.6× 78 0.4× 120 1.1× 29 0.4× 32 636
Kristin McLeod Norway 9 59 0.3× 106 0.5× 120 0.6× 64 0.6× 40 0.6× 17 331
Ade Iriani Sapitri Indonesia 10 67 0.3× 73 0.3× 143 0.8× 57 0.5× 91 1.3× 38 344
José Seabra Portugal 11 144 0.6× 141 0.6× 124 0.7× 43 0.4× 40 0.6× 18 316
Andreas Østvik Norway 15 83 0.4× 424 1.9× 431 2.3× 35 0.3× 63 0.9× 35 663
Clifford Yang United States 11 85 0.4× 377 1.7× 77 0.4× 356 3.4× 24 0.3× 22 673
Archana Laroia United States 12 153 0.7× 266 1.2× 37 0.2× 125 1.2× 24 0.3× 28 513

Countries citing papers authored by Pankaj K. Jain

Since Specialization
Citations

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

Fields of papers citing papers by Pankaj K. Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pankaj K. Jain. 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 Pankaj K. Jain. The network helps show where Pankaj K. Jain may publish in the future.

Co-authorship network of co-authors of Pankaj K. Jain

This figure shows the co-authorship network connecting the top 25 collaborators of Pankaj K. Jain. A scholar is included among the top collaborators of Pankaj K. Jain 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 Pankaj K. Jain. Pankaj K. Jain is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
2.
Jain, Pankaj K., et al.. (2023). Atherosclerotic plaque classification in carotid ultrasound images using machine learning and explainable deep learning. SHILAP Revista de lepidopterología. 4(2). 83–95. 10 indexed citations
3.
Jain, Pankaj K., Neeraj Sharma, Mannudeep K. Kalra, et al.. (2022). Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence paradigm for stroke risk assessment. Computers in Biology and Medicine. 149. 106017–106017. 25 indexed citations
4.
5.
Jain, Pankaj K., Luca Saba, Narendra N. Khanna, et al.. (2022). Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm. Journal of Cardiovascular Development and Disease. 9(10). 326–326. 31 indexed citations
6.
Jain, Pankaj K., Neeraj Sharma, Luca Saba, et al.. (2021). Unseen Artificial Intelligence—Deep Learning Paradigm for Segmentation of Low Atherosclerotic Plaque in Carotid Ultrasound: A Multicenter Cardiovascular Study. Diagnostics. 11(12). 2257–2257. 32 indexed citations
7.
Jain, Pankaj K., Neeraj Sharma, A Giannopoulos, et al.. (2021). Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound. Computers in Biology and Medicine. 136. 104721–104721. 81 indexed citations
8.
Jain, Pankaj K., Neeraj Sharma, Luca Saba, et al.. (2021). Automated deep learning-based paradigm for high-risk plaque detection in B-mode common carotid ultrasound scans: an asymptomatic Japanese cohort study. International Angiology. 41(1). 9–23. 29 indexed citations
9.
Jain, Pankaj K., Saurabh Gupta, Arnav Bhavsar, Aditya Nigam, & Neeraj Sharma. (2020). Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach. Medical & Biological Engineering & Computing. 58(3). 471–482. 26 indexed citations
10.
Saba, Luca, Pankaj K. Jain, Harman S. Suri, et al.. (2017). Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm. Journal of Medical Systems. 41(6). 98–98. 59 indexed citations
11.
Araki, Tadashi, Nobutaka Ikeda, Pankaj K. Jain, et al.. (2016). PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology. Computer Methods and Programs in Biomedicine. 128. 137–158. 64 indexed citations
12.
Araki, Tadashi, Pankaj K. Jain, Harman S. Suri, et al.. (2016). Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm. Computers in Biology and Medicine. 80. 77–96. 67 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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