Primož Kocbek

发表

Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening

Gregor Stiglic, Primoz Kocbek, Leona Cilar, 2019, KR4HC/ProHealth/TEAAM@AIME.

Using (Automated) Machine Learning and Drug Prescription Records to Predict Mortality and Polypharmacy in Older Type 2 Diabetes Mellitus Patients

Bogdan Gabrys, Gregor Stiglic, Simon Kocbek, 2019, ICONIP.

Building interpretable models for polypharmacy prediction in older chronic patients based on drug prescription records

T. Groza, G. Štiglic, Simon Kocbek, 2018, PeerJ.

An international cross-cultural study of nursing students' perceptions of caring.

G. Štiglic, R. Watson, P. Kocbek, 2019, Nurse education today.

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

Aziz Sheikh, Majda Pajnkihar, Nino Fijacko, 2019, Health Informatics J..

Early detection of type 2 diabetes mellitus using machine learning-based prediction models

A. Sheikh, G. Štiglic, P. Kocbek, 2020, Scientific Reports.

Interpretability of machine learning‐based prediction models in healthcare

Marinka Zitnik, Gregor Stiglic, Katrien Verbert, 2020, WIREs Data Mining Knowl. Discov..

The Antimicrobial Effect of Various Single-Strain and Multi-Strain Probiotics, Dietary Supplements or Other Beneficial Microbes against Common Clinical Wound Pathogens

A. Steyer, P. Kocbek, S. Fijan, 2022, Microorganisms.

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

G. Štiglic, P. Kocbek, N. Fijačko, 2019, Health Informatics J..

A Review of Mortality Risk Prediction Models in Smartphone Applications

Lucija Gosak, Leona Cilar, Gregor Štiglic, 2021, Journal of Medical Systems.