Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening. - Leon Kopitar; Leona Cilar; Primoz Kocbek; Gregor Stiglic (KR4HC/ProHealth/TEAAM@AIME, 2019)

Using (Automated) Machine Learning and Drug Prescription Records to Predict Mortality and Polypharmacy in Older Type 2 Diabetes Mellitus Patients. - Simon Kocbek; Primoz Kocbek; Tina Zupanic; Gregor Stiglic; Bogdan Gabrys (ICONIP (4), 2019)

Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data. - Primoz Kocbek; Nino Fijacko; Cristina Soguero-Ruíz; Karl Øyvind Mikalsen; Uros Maver; Petra Povalej Brzan; Andraz Stozer; Robert Jenssen; Stein Olav Skrøvseth; Gregor Stiglic (Comput. Math. Methods Medicine, 2019)

Challenges associated with missing data in electronic health records: A case study of a risk prediction model for diabetes using data from Slovenian primary care. - Gregor Stiglic; Primoz Kocbek; Nino Fijacko; Aziz Sheikh; Majda Pajnkihar (Health Informatics J., 2019)

Evaluation of Mobile Phone Mortality Risk Score Applications Using Data from the Electronic Medical Records. - Nino Fijacko; Lucija Gosak; Primoz Kocbek; Leona Cilar; Andrej Markota; Gregor Stiglic (MIE, 2020)

Local Interpretability of Calibrated Prediction Models: A Case of Type 2 Diabetes Mellitus Screening Test. - Simon Kocbek; Primoz Kocbek; Leona Cilar; Gregor Stiglic (CoRR, 2020)

Interpretability of machine learning-based prediction models in healthcare. - Gregor Stiglic; Primoz Kocbek; Nino Fijacko; Marinka Zitnik; Katrien Verbert; Leona Cilar (WIREs Data Mining Knowl. Discov., 2020)

A Review of Mortality Risk Prediction Models in Smartphone Applications. - Nino Fijacko; Ruth Masterson Creber; Lucija Gosak; Primoz Kocbek; Leona Cilar; Peter Creber; Gregor Stiglic (J. Medical Syst., 2021)

Generating Extremely Short Summaries from the Scientific Literature to Support Decisions in Primary Healthcare: A Human Evaluation Study. - Primoz Kocbek; Lucija Gosak; Kasandra Musovic; Gregor Stiglic (AIME, 2022)

Relevance of automated generated short summaries of scientific abstract: use case scenario in healthcare. - Gregor Stiglic; Kasandra Musovic; Lucija Gosak; Nino Fijacko; Primoz Kocbek (ICHI, 2022)

Improving Primary Healthcare Workflow Using Extreme Summarization of Scientific Literature Based on Generative AI. - Gregor Stiglic; Leon Kopitar; Lucija Gosak; Primoz Kocbek; Zhe He 001; Prithwish Chakraborty; Pablo Meyer 001; Jiang Bian 001 (CoRR, 2023)

Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare. - Leon Kopitar; Primoz Kocbek; Lucija Gosak; Gregor Stiglic (CoRR, 2024)

Large Language Models in Healthcare: Prompt Engineering Competition. - Primoz Kocbek; Lucija Gosak; Gregor Stiglic (ICHI, 2025)

UM_FHS at TREC 2024 PLABA: Exploration of Fine-tuning and AI agent approach for plain language adaptations of biomedical text. - Primoz Kocbek; Leon Kopitar; Zhihong Zhang; Emirhan Aydin; Maxim Topaz; Gregor Stiglic (CoRR, 2025)