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2020 – today
- 2024
[j22]Leon Kopitar
, Iztok Fister Jr., Gregor Stiglic:
Using Generative AI to Improve the Performance and Interpretability of Rule-Based Diagnosis of Type 2 Diabetes Mellitus. Inf. 15(3): 162 (2024)- [c46]Aditya Bhattacharya, Simone Stumpf, Lucija Gosak, Gregor Stiglic, Katrien Verbert:
EXMOS: Explanatory Model Steering through Multifaceted Explanations and Data Configurations. CHI 2024: 314:1-314:27 - [c45]Leon Kopitar, Gregor Stiglic, Leon Bedrac, Jiang Bian:
Personalized Meal Planning in Inpatient Clinical Dietetics Using Generative Artificial Intelligence: System Description. ICHI 2024: 326-331 - [c44]Yanshan Wang, Yifan Peng, Mei Liu, Xinning Gui, Zhengxing Huang, Gregor Stiglic:
Message from the Program Chairs; ICHI 2024. ICHI 2024: xxiii-xxiv - [i6]Aditya Bhattacharya, Simone Stumpf, Lucija Gosak, Gregor Stiglic, Katrien Verbert:
EXMOS: Explanatory Model Steering Through Multifaceted Explanations and Data Configurations. CoRR abs/2402.00491 (2024) - 2023
- [j21]Leon Kopitar, Peter Kokol, Gregor Stiglic:
Hybrid visualization-based framework for depressive state detection and characterization of atypical patients. J. Biomed. Informatics 147: 104535 (2023) - [j20]Carlo Combi, Julio C. Facelli, Peter Haddawy, John H. Holmes, Sabine Koch, Hongfang Liu, Jochen Meyer, Mor Peleg, Giuseppe Pozzi, Gregor Stiglic, Pierangelo Veltri, Christopher C. Yang:
The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19. J. Heal. Informatics Res. 7(2): 169-202 (2023) - [j19]Leona Cilar Budler, Lucija Gosak, Gregor Stiglic:
Review of artificial intelligence-based question-answering systems in healthcare. WIREs Data. Mining. Knowl. Discov. 13(2) (2023) - [c43]Carlo Combi, Julio C. Facelli, Peter Haddawy, John H. Holmes, Sabine Koch, Hongfang Liu, Jochen Meyer, Mor Peleg, Giuseppe Pozzi, Gregor Stiglic, Pierangelo Veltri, Christopher C. Yang:
Resuming HealthCare Informatics Research after CoViD-19: the HealthCare System Perspective. ICHI 2023: 760-762 - [c42]Aditya Bhattacharya, Jeroen Ooge, Gregor Stiglic, Katrien Verbert:
Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations. IUI 2023: 204-219 - [c41]Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner:
Workshop on Applied Data Science for Healthcare: Applications and New Frontiers of Generative Models for Healthcare. KDD 2023: 5893-5894 - [e3]Jose M. Juarez, Mar Marcos, Gregor Stiglic, Allan Tucker:
Artificial Intelligence in Medicine - 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12-15, 2023, Proceedings. Lecture Notes in Computer Science 13897, Springer 2023, ISBN 978-3-031-34343-8 [contents] - [e2]Shashi Shekhar, Zhi-Hua Zhou, Yao-Yi Chiang, Gregor Stiglic:
Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023. SIAM 2023, ISBN 978-1-61197-765-3 [contents] - [i5]Aditya Bhattacharya, Jeroen Ooge, Gregor Stiglic, Katrien Verbert:
Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations. CoRR abs/2302.10671 (2023) - [i4]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) - [i3]Aditya Bhattacharya, Simone Stumpf, Lucija Gosak, Gregor Stiglic, Katrien Verbert:
Lessons Learned from EXMOS User Studies: A Technical Report Summarizing Key Takeaways from User Studies Conducted to Evaluate The EXMOS Platform. CoRR abs/2310.02063 (2023) - 2022
- [j18]Jeroen Ooge, Gregor Stiglic, Katrien Verbert:
Explaining artificial intelligence with visual analytics in healthcare. WIREs Data Mining Knowl. Discov. 12(1) (2022) - [c40]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 - [c39]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 - [c38]Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner:
Workshop on Applied Data Science for Healthcare (DSHealth): Transparent and Human-centered AI. KDD 2022: 4908-4909 - 2021
- [j17]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) - [c37]Fei Wang, Prithwish Chakraborty, Tao Xu, Pei-Yun Sabrina Hsueh, Xudong Sun, Gregor Stiglic, Gracy Crane, Jiang Bian, Laleh Haghverdi, Lixia Yao, Florian Buettner:
KDD Health Day/DSHealth 2021: Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare: State of XAI and Trustworthiness in Health. KDD 2021: 4159-4160 - 2020
- [j16]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) - [c36]Leona Cilar, Majda Pajnkihar, Gregor Stiglic:
Interpreting influence of feature ranking in derivation of prediction models for screening questionnaires optimization. ICDM 2020: 67-78 - [c35]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
- [j15]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) - [j14]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) - [c34]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 - [c33]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 - [e1]Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic:
Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11979, Springer 2019, ISBN 978-3-030-37445-7 [contents] - 2018
- [j13]Xia Hu, Gregor Stiglic, Fei Wang:
Special Issue on Data Mining in Health Informatics. J. Heal. Informatics Res. 2(4): 367-369 (2018) - [c32]Andrej Fajfar, Manuel Campos, Francisco Palacios, Bernardo Cánovas-Segura, Gregor Stiglic, Roque Marín:
Risk Factors for Development of Antibiotic Resistance of Enterococcus Faecium to Vancomycin. A Subgroup Discovery Approach. CAEPIA 2018: 285-295 - 2017
- [c31]Ales Zamuda, Christine Zarges, Gregor Stiglic, Goran Hrovat:
Stability selection using a genetic algorithm and logistic linear regression on healthcare records. GECCO (Companion) 2017: 143-144 - 2016
- [c30]Fei Wang, Gregor Stiglic, Mihaela van der Schaar, David A. Sontag, Christopher C. Yang:
Data Mining for Medical Informatics (DMMI) - Learning Health. AMIA 2016 - 2015
- [j12]Fei Wang, Gregor Stiglic, Zoran Obradovic, Ian Davidson:
Guest editorial: Special issue on data mining for medicine and healthcare. Data Min. Knowl. Discov. 29(4): 867-870 (2015) - [j11]Igor Pernek, Gregorij Kurillo, Gregor Stiglic, Ruzena Bajcsy:
Recognizing the intensity of strength training exercises with wearable sensors. J. Biomed. Informatics 58: 145-155 (2015) - [j10]Goran Hrovat, Iztok Fister Jr., Katsiaryna Yermak, Gregor Stiglic, Iztok Fister:
Interestingness measure for mining sequential patterns in sports. J. Intell. Fuzzy Syst. 29(5): 1981-1994 (2015) - [j9]Nino Fijacko, Petra Povalej Brzan, Gregor Stiglic:
Mobile Applications for Type 2 Diabetes Risk Estimation: a Systematic Review. J. Medical Syst. 39(10): 124:1-124:10 (2015) - [c29]Sandro Radovanovic, Milan Vukicevic, Ana Kovacevic, Gregor Stiglic, Zoran Obradovic:
Domain knowledge Based Hierarchical Feature Selection for 30-Day Hospital Readmission Prediction. AIME 2015: 96-100 - [c28]Fei Wang, Gregor Stiglic:
Data Analytics in Healthcare Informatics. ICHI 2015: 444 - [c27]Milan Vukicevic, Sandro Radovanovic, Ana Kovacevic, Gregor Stiglic, Zoran Obradovic:
Improving Hospital Readmission Prediction Using Domain Knowledge Based Virtual Examples. KMO 2015: 695-706 - [c26]David J. Odgers, Rave Harpaz, Alison Callahan, Gregor Stiglic, Nigam H. Shah:
Analyzing Search Behavior of Healthcare Professionals for Drug Safety Surveillance. Pacific Symposium on Biocomputing 2015: 306-317 - 2014
- [j8]Goran Hrovat, Gregor Stiglic, Peter Kokol, Milan Ojstersek:
Contrasting temporal trend discovery for large healthcare databases. Comput. Methods Programs Biomed. 113(1): 251-257 (2014) - [c25]Gregor Stiglic, Fei Wang, Adam Davey, Zoran Obradovic:
Readmission Classification Using Stacked Regularized Logistic Regression Models. AMIA 2014 - [c24]Gregor Stiglic:
Tutorial: Developing and Deploying Healthcare Predictive Models in R. ICHI 2014: 363 - 2013
- [c23]Gregor Stiglic, Adam Davey, Zoran Obradovic:
Temporal Evaluation of Risk Factors for Acute Myocardial Infarction Readmissions. ICHI 2013: 557-562 - [c22]Andrej Duh, Gregor Stiglic, Dean Korosak:
Enhancing Identification of Opinion Spammer Groups. MindTrek 2013: 326 - 2012
- [j7]Peter Kokol, Sandi Pohorec, Gregor Stiglic, Vili Podgorelec:
Evolutionary design of decision trees for medical application. WIREs Data Mining Knowl. Discov. 2(3): 237-254 (2012) - [c21]Igor Pernek, Gregor Stiglic, Peter Kokol:
How Hard Am I Training? Using Smart Phones to Estimate Sport Activity Intensity. ICDCS Workshops 2012: 65-68 - 2011
- [j6]Simon Kocbek, Rune Sætre, Gregor Stiglic, Jin-Dong Kim, Igor Pernek, Yoshimasa Tsuruoka, Peter Kokol, Sophia Ananiadou, Jun'ichi Tsujii:
AGRA: analysis of gene ranking algorithms. Bioinform. 27(8): 1185-1186 (2011) - [c20]Peter Kokol, Gregor Stiglic:
PRIMER ICT: A new blended learning paradigm for teaching ICT skills to older people. CBMS 2011: 1-5 - [c19]Simon Kocbek, Rune Sætre, Gregor Stiglic, Jin-Dong Kim, Igor Pernek, Yoshimasa Tsuruoka, Peter Kokol, Sophia Ananiadou, Jun'ichi Tsujii:
Poster: Analysis of gene ranking algorithms with extraction of relevant biomedical concepts from PubMed publications. ICCABS 2011: 249 - [c18]Gregor Stiglic, Peter Kokol:
Interpretability of Sudden Concept Drift in Medical Informatics Domain. ICDM Workshops 2011: 609-613 - [c17]Gregor Stiglic, Simon Kocbek, Igor Pernek, Peter Kokol:
Tuning Decision Tree Models by Imposing Visual Constraints. MLDM Posters 2011: 38-48 - 2010
- [j5]Gregor Stiglic, Mateja Bajgot, Peter Kokol:
Gene set enrichment meta-learning analysis: next- generation sequencing versus microarrays. BMC Bioinform. 11: 176 (2010) - [j4]Gregor Stiglic, Juan José Rodríguez Diez, Peter Kokol:
Finding optimal classifiers for small feature sets in genomics and proteomics. Neurocomputing 73(13-15): 2346-2352 (2010) - [c16]Gregor Stiglic, Igor Pernek, Peter Kokol:
Identification of Specific Gene Expression Signatures in Oncology. BIOCOMP 2010: 760-765 - [c15]Simon Kocbek, Gregor Stiglic, Igor Pernek, Peter Kokol:
Stability of different feature selection methods for selecting protein sequence descriptors in protein solubility classification problem. CBMS 2010: 50-55
2000 – 2009
- 2009
- [j3]Miljenko Krizmaric, Mateja Verlic, Gregor Stiglic, Stefek Grmec, Peter Kokol:
Intelligent analysis in predicting outcome of out-of-hospital cardiac arrest. Comput. Methods Programs Biomed. 95(2-S1): 22-32 (2009) - [c14]Gregor Stiglic, Simon Kocbek, Peter Kokol:
Unsupervised variance based preprocessing of microarray data. CBMS 2009: 1-4 - [r1]Petra Povalej, Mateja Verlic, Gregor Stiglic:
Discovery Systems. Encyclopedia of Complexity and Systems Science 2009: 1982-2002 - 2008
- [c13]Mateja Verlic, Gregor Stiglic, Simon Kocbek, Peter Kokol:
Sentiment in Science - A Case Study of CBMS Contributions in Years 2003 to 2007. CBMS 2008: 138-143 - [c12]Gregor Stiglic, Juan J. Rodríguez Diez, Peter Kokol:
Feature Selection and Classification for Small Gene Sets. PRIB 2008: 121-131 - [p1]Gregor Stiglic, Nawaz Khan, Peter Kokol:
Knowledge Extraction from Microarray Datasets Using Combined Multiple Models to Predict Leukemia Types. Data Mining: Foundations and Practice 2008: 339-352 - 2007
- [j2]Gregor Stiglic, Matej Mertik, Peter Kokol, Maurizio Pighin:
Detecting Fault Modules Using Bioinformatics Techniques. Int. J. Softw. Eng. Knowl. Eng. 17(1): 153 (2007) - [j1]Gregor Stiglic, Peter Kokol:
Evolutionary approach to combined multiple models tuning. Int. J. Knowl. Based Intell. Eng. Syst. 11(4): 227-235 (2007) - [c11]Gregor Stiglic, Peter Kokol:
Effectiveness of Rotation Forest in Meta-learning Based Gene Expression Classification. CBMS 2007: 243-250 - [c10]Gregor Stiglic, Nawaz Khan, Mateja Verlic, Peter Kokol:
Gene Expression Analysis of Leukemia Samples Using Visual Interpretation of Small Ensembles: A Case Study. PRIB 2007: 189-197 - 2006
- [c9]Gregor Stiglic, Matej Mertik, Vili Podgorelec, Peter Kokol:
Using Visual Interpretation of Small Ensembles in Microarray Analysis. CBMS 2006: 691-695 - [c8]Matej Mertik, Mitja Lenic, Gregor Stiglic, Peter Kokol:
Estimating Software Quality with Advanced Data Mining Techniques. ICSEA 2006: 19 - [c7]Gregor Stiglic, Peter Kokol:
Evolutionary Tuning of Combined Multiple Models. KES (2) 2006: 1297-1304 - 2005
- [c6]Miljenko Krizmaric, Tanja Zmauc, Dusanka Micetic Turk, Gregor Stiglic, Peter Kokol:
Time Allocation Simulation Model of Clean and Dirty Pathways in Hospital Environment. CBMS 2005: 123-127 - 2004
- [c5]Peter Kokol, Petra Povalej, Mitja Lenic, Gregor Stiglic:
Building Classifier Cellular Automata. ACRI 2004: 823-830 - [c4]Gregor Stiglic, Peter Kokol:
Sizing tumors with TNM Classifications and Rough Sets Method. CBMS 2004: 221-223 - [c3]Gregor Stiglic, Peter Kokol:
Bioinformatics approach to data mining of software bases. IASTED Conf. on Software Engineering and Applications 2004: 786-789 - [c2]Petra Povalej, Gregor Stiglic, Peter Kokol, Bruno Stiglic, Irene Litvan, Dusan Flisar:
Verifying Clinical Criteria for Parkinsonian Disorders with CART Decision Trees. KES 2004: 1018-1024 - [c1]Petra Povalej, Mitja Lenic, Gregor Stiglic, Tatjana Welzer, Peter Kokol:
Improving Classification Accuracy Using Cellular Automata. KES 2004: 1025-1031
Coauthor Index
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last updated on 2024-10-21 20:33 CEST by the dblp team
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