Shreyasi Pathak

648 total citations · 1 hit paper
12 papers, 315 citations indexed

About

Shreyasi Pathak is a scholar working on Artificial Intelligence, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shreyasi Pathak has authored 12 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 3 papers in Molecular Biology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shreyasi Pathak's work include Biomedical Text Mining and Ontologies (3 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Shreyasi Pathak is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Shreyasi Pathak collaborates with scholars based in Netherlands, Germany and India. Shreyasi Pathak's co-authors include Christin Seifert, Maurice van Keulen, Elisa Nguyen, Meike Nauta, Jörg Schlötterer, Jan Trienes, Michel J. A. M. van Putten, Sunil B. Nagaraj, Gwenn Englebienne and Nitin Agarwal and has published in prestigious journals such as ACM Computing Surveys, International Journal of Environmental Research and Public Health and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

In The Last Decade

Shreyasi Pathak

11 papers receiving 306 citations

Hit Papers

align trajectories sort by overperformance

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.

From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI

2023 205 citations Meike Nauta, Jan Trienes et al. ACM Computing Surveys profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shreyasi Pathak Netherlands	7	200	49	43	27	25	12	315
Surabhi Adhikari India	10	142 0.7×	11 0.2×	42 1.0×	20 0.7×	37 1.5×	13	299
Ivan Donadello Italy	10	181 0.9×	10 0.2×	28 0.7×	32 1.2×	7 0.3×	22	261
Hanjie Chen United States	6	235 1.2×	6 0.1×	39 0.9×	28 1.0×	18 0.7×	10	347
Bernd Malle Austria	4	165 0.8×	8 0.2×	33 0.8×	39 1.4×	20 0.8×	4	266
Karthik Sekaran India	9	64 0.3×	14 0.3×	11 0.3×	15 0.6×	15 0.6×	32	306
Zabir Al Nazi Bangladesh	8	102 0.5×	57 1.2×	57 1.3×	19 0.7×	34 1.4×	13	268
Ruihua Song China	7	144 0.7×	12 0.2×	23 0.5×	87 3.2×	21 0.8×	20	322
Udo Schlegel Germany	5	170 0.8×	9 0.2×	26 0.6×	84 3.1×	5 0.2×	19	263
Tharindu Kaluarachchi New Zealand	5	164 0.8×	43 0.9×	9 0.2×	54 2.0×	9 0.4×	11	320
Anson Ho Canada	3	94 0.5×	13 0.3×	12 0.3×	24 0.9×	6 0.2×	8	217

Countries citing papers authored by Shreyasi Pathak

Since Specialization

Citations

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

Fields of papers citing papers by Shreyasi Pathak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shreyasi Pathak

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

All Works

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12 of 12 papers shown

Nauta, Meike, Jan Trienes, Shreyasi Pathak, et al.. (2023). From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI. ACM Computing Surveys. 55(13s). 1–42. 205 indexed citations breakdown →

Nauta, Meike, et al.. (2023). Benchmarking eXplainable AI - A Survey on Available Toolkits and Open Challenges. Universitätsbibliographie, Universität Duisburg-Essen. 6665–6673. 6 indexed citations

Nauta, Meike, Jan Trienes, Shreyasi Pathak, et al.. (2022). From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI. arXiv (Cornell University). 14 indexed citations

Pathak, Shreyasi, et al.. (2022). Channel Contribution in Deep Learning Based Automatic Sleep Scoring—How Many Channels Do We Need?. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 494–505. 7 indexed citations

Pathak, Shreyasi, et al.. (2021). Multimodal Machine Learning for 30-Days Post-Operative Mortality Prediction of Elderly Hip Fracture Patients. University of Twente Research Information. 508–516. 3 indexed citations

Pathak, Shreyasi, et al.. (2021). STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoring. Artificial Intelligence in Medicine. 114. 102038–102038. 45 indexed citations

Pathak, Shreyasi, et al.. (2020). Automatic Process Comparison for Subpopulations: Application in Cancer Care. International Journal of Environmental Research and Public Health. 17(16). 5707–5707. 6 indexed citations

Nguyen, Elisa, et al.. (2020). A Hybrid Text Classification and Language Generation Model for Automated Summarization of Dutch Breast Cancer Radiology Reports. University of Twente Research Information. 72–81. 7 indexed citations

Pathak, Shreyasi, et al.. (2020). Human-in-the-loop Language-agnostic Extraction of Medication Data from Highly Unstructured Electronic Health Records. University of Twente Research Information. 644–650.

10.

Pathak, Shreyasi, et al.. (2019). Post-Structuring Radiology Reports of Breast Cancer Patients for Clinical Quality Assurance. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17(6). 1883–1894. 12 indexed citations

11.

Pathak, Shreyasi, et al.. (2018). Automatic Structuring of Breast Cancer Radiology Reports for Quality Assurance. Universitätsbibliographie, Universität Duisburg-Essen. 21. 732–739. 4 indexed citations

12.

Agarwal, Nitin, et al.. (2014). A system for stoppage pattern extraction from public bus GPS traces in developing regions. 72–75. 6 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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