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

M. Nauta, J. Trienes, S. Pathak, E. Nguyen, M. Peters, Y. Schmitt, J. Schlötterer, M. van Keulen, and C. Seifert. ACM Comput. Surv., 55 (13s): 295:1-295:42 (2023)

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Shreyasi Mishra

Trilochan Pathak

Nemaí Chand Pathak

Krishna Mani Pathak

Bhim Sen Pathak

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Benchmarking eXplainable AI - A Survey on Available Toolkits and Open Challenges.P. Le, M. Nauta, V. Nguyen, S. Pathak, J. Schlötterer, and C. Seifert. IJCAI, page 6665-6673. ijcai.org, (2023)Comparing Process Models for Patient Populations: Application in Breast Cancer Care.F. Marazza, F. Bukhsh, O. Vijlbrief, J. Geerdink, S. Pathak, M. van Keulen, and C. Seifert. Business Process Management Workshops, volume 362 of Lecture Notes in Business Information Processing, page 496-507. Springer, (2019)Post-Structuring Radiology Reports of Breast Cancer Patients for Clinical Quality Assurance.S. Pathak, J. van Rossen, O. Vijlbrief, J. Geerdink, C. Seifert, and M. van Keulen. IEEE ACM Trans. Comput. Biol. Bioinform., 17 (6): 1883-1894 (2020)From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI.M. Nauta, J. Trienes, S. Pathak, E. Nguyen, M. Peters, Y. Schmitt, J. Schlötterer, M. van Keulen, and C. Seifert. ACM Comput. Surv., 55 (13s): 295:1-295:42 (2023)From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI.M. Nauta, J. Trienes, S. Pathak, E. Nguyen, M. Peters, Y. Schmitt, J. Schlötterer, M. van Keulen, and C. Seifert. CoRR, (2022)Weakly Supervised Learning for Breast Cancer Prediction on Mammograms in Realistic Settings.S. Pathak, J. Schlötterer, J. Geerdink, O. Vijlbrief, M. van Keulen, and C. Seifert. CoRR, (2023)Human-in-the-loop Language-agnostic Extraction of Medication Data from Highly Unstructured Electronic Health Records.F. Ruis, S. Pathak, J. Geerdink, J. Hegeman, C. Seifert, and M. van Keulen. ICDM (Workshops), page 644-650. IEEE, (2020)Multimodal Machine Learning for 30-Days Post-Operative Mortality Prediction of Elderly Hip Fracture Patients.B. Yenidogan, S. Pathak, J. Geerdink, J. Hegeman, and M. van Keulen. ICDM (Workshops), page 508-516. IEEE, (2021)Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges.S. Pathak, J. Schlötterer, J. Veltman, J. Geerdink, M. van Keulen, and C. Seifert. CoRR, (2024)STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoring.S. Pathak, C. Lu, S. Nagaraj, M. van Putten, and C. Seifert. Artif. Intell. Medicine, (2021)

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Disambiguation of "Pathak, Shreyasi"

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

Please choose a person to relate this publication to

Shreyasi Mishra

Trilochan Pathak

Nemaí Chand Pathak

Krishna Mani Pathak

Bhim Sen Pathak

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Pathak, Shreyasi"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI.

Please choose a person to relate this publication to

Shreyasi Mishra

Trilochan Pathak

Nemaí Chand Pathak

Krishna Mani Pathak

Bhim Sen Pathak

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI.