Dragutin Petković

Institute of Electrical and Electronics Engineers — United States

Computer Science · Physical Sciences

28h-index10.3kcitations102works0.02yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Image Retrieval and Classification Techniques(28), Advanced Image and Video Retrieval Techniques(25), Video Analysis and Summarization(18), Software Engineering Techniques and Practices(13), Image and Object Detection Techniques(12)

Publications102 total

1241 Dying to know campaign: how communities embrace ACP; insights and tips from the field!
2025Open Access
GenAI: Our Tool Or Our Future Master?
2025Open Access
Issues and Concerns About GenAI and How We Can Smartly Use It in Education
Proceedings of the AAAI Symposium Series·2025Open Access
GenAI: Our Tool Or Our Future Master?
IEEE Transactions on Technology and Society·2025
It is Not “Accuracy vs. Explainability”—We Need Both for Trustworthy AI Systems
IEEE Transactions on Technology and Society·2023· 51 cited
Introduction
Elsevier eBooks·2023· 2 cited
List of contributors
Elsevier eBooks·2023
Explainable Deep Learning AI
Elsevier eBooks·2023· 5 cited
Preface
Elsevier eBooks·2023
PhenClust, a standalone tool for identifying trends within sets of biological phenotypes using semantic similarity and the Unified Medical Language System metathesaurus
JAMIA Open·2021· 6 citedOpen Access
Search and visualization of gene-drug-disease interactions for pharmacogenomics and precision medicine research using GeneDive
Journal of Biomedical Informatics·2021· 12 citedOpen Access
Random Forest Model and Sample Explainer for Non-experts in Machine Learning – Two Case Studies
Lecture notes in computer science·2021· 5 cited
AI Ethics and Values in Biomedicine – Technical Challenges and Solutions
2019· 4 citedOpen Access
RFEX: Simple Random Forest Model and Sample Explainer for non-Machine Learning experts
2019Open Access
PathFXweb: a web application for identifying drug safety and efficacy phenotypes
Bioinformatics·2019· 9 citedOpen Access
From Explaining How Random Forest Classifier Predicts Learning of Software Engineering Teamwork to Guidance for Educators
2018· 11 cited
Improving the explainability of Random Forest classifier – user centered approach
2017· 92 citedOpen Access
GeneDive: A gene interaction search and visualization tool to facilitate precision medicine
2017· 9 citedOpen Access
Machine learning and deep analytics for biocomputing: call for better explainability
2017· 13 citedOpen Access
Using the random forest classifier to assess and predict student learning of Software Engineering Teamwork
2016· 54 cited
page 1 of 6Next →

Frequent Co-authors

Myron Flickner(15), W. Niblack(15), Rainer Todtenhoefer(9), Dulce Ponceleón(7), John W. Hafner(5), D. Lee(5), P. Yanker(5), Ronald Barber(5), Savitha Srinivasan(5), Arnon Amir(5), Gary D. Thompson(5), Jonathan Ashley(4), James Lee Hafner(4), Shihong Huang(4), Jorge L. C. Sanz(4), Byron Dom(3), Carlton W. Niblack(3), W. Equitz(3), Denis Lee(3), Russ B. Altman(3)