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2020 – today
- 2024
[i4]Leon Kopitar, Primoz Kocbek, Lucija Gosak, Gregor Stiglic:
Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare. CoRR abs/2411.11635 (2024)- 2023
- [i3]Gregor Stiglic, Leon Kopitar, Lucija Gosak, Primoz Kocbek, Zhe He, Prithwish Chakraborty, Pablo Meyer, Jiang Bian:
Improving Primary Healthcare Workflow Using Extreme Summarization of Scientific Literature Based on Generative AI. CoRR abs/2307.15715 (2023) - 2022
- [c5]Primoz Kocbek
, Lucija Gosak, Kasandra Musovic, Gregor Stiglic:
Generating Extremely Short Summaries from the Scientific Literature to Support Decisions in Primary Healthcare: A Human Evaluation Study. AIME 2022: 373-382 - [c4]Gregor Stiglic, Kasandra Musovic, Lucija Gosak, Nino Fijacko, Primoz Kocbek:
Relevance of automated generated short summaries of scientific abstract: use case scenario in healthcare. ICHI 2022: 599-605 - 2021
- [j4]Nino Fijacko, Ruth Masterson Creber, Lucija Gosak, Primoz Kocbek, Leona Cilar, Peter Creber, Gregor Stiglic:
A Review of Mortality Risk Prediction Models in Smartphone Applications. J. Medical Syst. 45(12): 107 (2021) - 2020
- [j3]Gregor Stiglic, Primoz Kocbek, Nino Fijacko, Marinka Zitnik, Katrien Verbert, Leona Cilar:
Interpretability of machine learning-based prediction models in healthcare. WIREs Data Mining Knowl. Discov. 10(5) (2020) - [c3]Nino Fijacko, Lucija Gosak, Primoz Kocbek, Leona Cilar, Andrej Markota, Gregor Stiglic:
Evaluation of Mobile Phone Mortality Risk Score Applications Using Data from the Electronic Medical Records. MIE 2020: 1273-1274 - [i2]Gregor Stiglic, Primoz Kocbek, Nino Fijacko, Marinka Zitnik, Katrien Verbert, Leona Cilar:
Interpretability of machine learning based prediction models in healthcare. CoRR abs/2002.08596 (2020) - [i1]Simon Kocbek, Primoz Kocbek, Leona Cilar, Gregor Stiglic:
Local Interpretability of Calibrated Prediction Models: A Case of Type 2 Diabetes Mellitus Screening Test. CoRR abs/2006.13815 (2020)
2010 – 2019
- 2019
- [j2]Primoz Kocbek, Nino Fijacko, Cristina Soguero-Ruíz, Karl Øyvind Mikalsen, Uros Maver, Petra Povalej Brzan, Andraz Stozer, Robert Jenssen, Stein Olav Skrøvseth, Gregor Stiglic:
Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data. Comput. Math. Methods Medicine 2019: 2059851:1-2059851:13 (2019) - [j1]Gregor Stiglic, Primoz Kocbek, Nino Fijacko, Aziz Sheikh, Majda Pajnkihar:
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. Health Informatics J. 25(3) (2019) - [c2]Leon Kopitar, Leona Cilar, Primoz Kocbek, Gregor Stiglic:
Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening. KR4HC/ProHealth/TEAAM@AIME 2019: 108-119 - [c1]Simon Kocbek, Primoz Kocbek, Tina Zupanic, Gregor Stiglic, Bogdan Gabrys:
Using (Automated) Machine Learning and Drug Prescription Records to Predict Mortality and Polypharmacy in Older Type 2 Diabetes Mellitus Patients. ICONIP (4) 2019: 624-632
Coauthor Index
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