Yadunath Pathak

877 total citations · 1 hit paper
19 papers, 619 citations indexed

About

Yadunath Pathak is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yadunath Pathak has authored 19 papers receiving a total of 619 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Biomedical Engineering and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yadunath Pathak's work include Medical Imaging Techniques and Applications (5 papers), Advanced X-ray and CT Imaging (4 papers) and Machine Learning in Bioinformatics (2 papers). Yadunath Pathak is often cited by papers focused on Medical Imaging Techniques and Applications (5 papers), Advanced X-ray and CT Imaging (4 papers) and Machine Learning in Bioinformatics (2 papers). Yadunath Pathak collaborates with scholars based in India, Ireland and South Korea. Yadunath Pathak's co-authors include Piyush Kumar Shukla, K. V. Arya, Prashant Kumar Shukla, Saurabh Singh, Akhilesh Tiwari, Shailendra Tiwari, Poonam Sharma, M. A. Rizvi, Anoop Chaturvedi and Kuldeep Kaur and has published in prestigious journals such as SHILAP Revista de lepidopterología, Multimedia Tools and Applications and IEEE/ACM Transactions on Computational Biology and Bioinformatics.

In The Last Decade

Yadunath Pathak

18 papers receiving 591 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep Transfer Learning Based Classification Model for COVID-19 Disease

2020 329 citations Yadunath Pathak, Prashant Kumar Shukla et al. IRBM profile →

Peers

Yadunath Pathak

RNMI

CVPR

CNC

Vaishali India

Subrato Bharati Bangladesh

Subhankar Ghosh India

Shiva Toumaj Iran

Eswaran Perumal India

Md. Rezwanul Haque Bangladesh

Shailendra Tiwari India

Mohammed Alawad United States

M.A. Abo-Elsoud Egypt

Apeksha Koul India

Vaishali India

Yadunath Pathak

393 ×1.2

RNMI

295 ×1.0

91 ×0.7

CVPR

79 ×1.3

43 ×1.0

CNC

Citations per year, relative to Yadunath Pathak Yadunath Pathak (= 1×) peers Vaishali

Countries citing papers authored by Yadunath Pathak

Since Specialization

Citations

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

Fields of papers citing papers by Yadunath Pathak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yadunath Pathak

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Pathak, Yadunath, et al.. (2025). A Comparative Evaluation of Machine Learning Models for Detecting Human Falls Using Wearable Sensors. 1–6.

Semwal, Vijay Bhaskar, et al.. (2024). Inverse Kinematic Solution Using Neural Networks for Multimodal Inputs and Optimization in Constrained Workspace. IEEE Sensors Letters. 9(1). 1–4. 1 indexed citations

Pathak, Yadunath, Gillian Horgan, Hiten D. Mistry, et al.. (2024). Healthcare providers’ experiences of maternity care service delivery during the COVID-19 pandemic in the United Kingdom: a follow-up systematic review and qualitative evidence synthesis. SHILAP Revista de lepidopterología. 5. 1470674–1470674. 2 indexed citations

Bhadoria, Robin Singh, et al.. (2022). Bunch graph based dimensionality reduction using auto-encoder for character recognition. Multimedia Tools and Applications. 81(22). 32093–32115. 8 indexed citations

Chatterjee, Parag, Robin Singh Bhadoria, & Yadunath Pathak. (2022). 5G and Beyond. 1 indexed citations

Shukla, Prashant Kumar, Piyush Kumar Shukla, Anoop Chaturvedi, et al.. (2021). A Novel Machine Learning Model to Predict the Staying Time of International Migrants. International Journal of Artificial Intelligence Tools. 30(2). 2150002–2150002. 39 indexed citations

Pathak, Yadunath, et al.. (2020). Deep Transfer Learning Based Classification Model for COVID-19 Disease. IRBM. 43(2). 87–92. 329 indexed citations breakdown →

Pathak, Yadunath, Piyush Kumar Shukla, & K. V. Arya. (2020). Deep Bidirectional Classification Model for COVID-19 Disease Infected Patients. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18(4). 1234–1241. 67 indexed citations

Sharma, Dilip Kumar, et al.. (2020). Artificial Immune Systems-Based Classification Model for Code-Mixed Social Media Data. IRBM. 43(2). 120–129. 10 indexed citations

10.

Singh, Vibhav Prakash, Rajeev Srivastava, Yadunath Pathak, Shailendra Tiwari, & Kuldeep Kaur. (2019). Content-based image retrieval based on supervised learning and statistical-based moments. Modern Physics Letters B. 33(19). 1950213–1950213. 14 indexed citations

11.

Tiwari, Shailendra, et al.. (2019). Computed tomography reconstruction on distributed storage using hybrid regularization approach. Modern Physics Letters B. 33(6). 1950063–1950063. 11 indexed citations

12.

Pathak, Yadunath, K. V. Arya, & Shailendra Tiwari. (2018). Low-dose CT image reconstruction using gain intervention-based dictionary learning. Modern Physics Letters B. 32(14). 1850148–1850148. 30 indexed citations

13.

Pathak, Yadunath, K. V. Arya, & Shailendra Tiwari. (2018). Fourth-order partial differential equations based anisotropic diffusion model for low-dose CT images. Modern Physics Letters B. 32(25). 1850300–1850300. 20 indexed citations

14.

Pathak, Yadunath, K. V. Arya, & Shailendra Tiwari. (2018). An efficient low-dose CT reconstruction technique using partial derivatives based guided image filter. Multimedia Tools and Applications. 78(11). 14733–14752. 10 indexed citations

15.

Pathak, Yadunath, K. V. Arya, & Shailendra Tiwari. (2018). Feature selection for image steganalysis using levy flight-based grey wolf optimization. Multimedia Tools and Applications. 78(2). 1473–1494. 59 indexed citations

16.

Pathak, Yadunath, et al.. (2016). Performance Study of Evolutionary Algorithms for Structure Stability Analysis of Al_n (n = 2–22). Quantum Matter. 5(3). 322–329. 3 indexed citations

17.

Arya, K. V., Yadunath Pathak, & Shailendra Tiwari. (2016). Regularization Based Modified SART Iterative Method for CT Image Reconstruction. 217–222. 5 indexed citations

18.

Pathak, Yadunath, Prashant Singh Rana, Pramod Kumar Singh, & Mukesh Saraswat. (2015). Protein structure prediction (RMSD ≤ 5 Å) using machine learning models. International Journal of Data Mining and Bioinformatics. 14(1). 71–71. 9 indexed citations

19.

Pathak, Yadunath, et al.. (2015). Classification of Protein Structure (RMSD <= 6A˚) using Physicochemical Properties. International Journal of Bio-Science and Bio-Technology. 7(6). 141–150. 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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