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2020 – today
- 2023
[i2]Gregor Guncar, Matjaz Kukar, Tim Smole, Saso Moskon, Tomaz Vovko, Simon Podnar, Peter Cernelc, Miran Brvar, Mateja Notar, Manca Köster, Marjeta Tusek Jelenc, Marko Notar:
Differentiating Viral and Bacterial Infections: A Machine Learning Model Based on Routine Blood Test Values. CoRR abs/2305.07877 (2023)- 2021
- [j18]Tim Smole
, Bojan Zunkovic, Matej Piculin, Enja Kokalj, Marko Robnik-Sikonja, Matjaz Kukar, Dimitrios I. Fotiadis, Vasileios C. Pezoulas, Nikolaos S. Tachos, Fausto Barlocco, Francesco Mazzarotto, Dejana Popovic, Lars Maier, Lazar U. Velicki, Guy A. MacGowan, Iacopo Olivotto, Nenad Filipovic, Djordje G. Jakovljevic, Zoran Bosnic:
A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy. Comput. Biol. Medicine 135: 104648 (2021) - 2020
- [i1]Matjaz Kukar, Gregor Guncar, Tomaz Vovko, Simon Podnar, Peter Cernelc, Miran Brvar, Mateja Zalaznik, Mateja Notar, Saso Moskon, Marko Notar:
COVID-19 diagnosis by routine blood tests using machine learning. CoRR abs/2006.03476 (2020)
2010 – 2019
- 2019
- [j17]Rok Rupnik, Matjaz Kukar, Petar Vracar, Domen Kosir, Darko Pevec, Zoran Bosnic:
AgroDSS: A decision support system for agriculture and farming. Comput. Electron. Agric. 161: 260-271 (2019) - [j16]Boris Petelin, Igor Kononenko, Vlado Malacic, Matjaz Kukar:
Frequent subgraph mining in oceanographic multi-level directed graphs. Int. J. Geogr. Inf. Sci. 33(10): 1936-1959 (2019) - 2018
- [j15]Jana Faganeli Pucer, Matjaz Kukar:
A topological approach to delineation and arrhythmic beats detection in unprocessed long-term ECG signals. Comput. Methods Programs Biomed. 164: 159-168 (2018) - 2015
- [j14]Boris Petelin, Igor Kononenko, Vlado Malacic, Matjaz Kukar:
Dynamic fuzzy paths and cycles in multi-level directed graphs. Eng. Appl. Artif. Intell. 37: 194-206 (2015) - [c20]Miha Drole, Petar Vracar, Ante Panjkota, Ivo Stancic, Josip Music, Igor Kononenko, Matjaz Kukar:
Learning from depth sensor data using inductive logic programming. ICAT 2015: 1-6 - 2014
- [c19]Lovro Subelj, Zoran Bosnic, Matjaz Kukar, Marko Bajec:
Automatization of the Stream Mining Process. CAiSE 2014: 409-423 - 2013
- [j13]Boris Petelin, Igor Kononenko, Vlado Malacic, Matjaz Kukar:
Multi-level association rules and directed graphs for spatial data analysis. Expert Syst. Appl. 40(12): 4957-4970 (2013) - [j12]Igor Kononenko, Erik Strumbelj, Zoran Bosnic, Darko Pevec, Matjaz Kukar, Marko Robnik-Sikonja:
Explanation and Reliability of Individual Predictions. Informatica (Slovenia) 37(1): 41-48 (2013) - 2012
- [c18]Anze Pecar, Miha Zidar, Matjaz Kukar:
Reservoir sampling techniques in modern data analysis. BCI 2012: 247-250 - 2011
- [j11]Matjaz Kukar, Igor Kononenko, Ciril Groselj:
Modern parameterization and explanation techniques in diagnostic decision support system: A case study in diagnostics of coronary artery disease. Artif. Intell. Medicine 52(2): 77-90 (2011) - [j10]Luka Sajn, Matjaz Kukar:
Image processing and machine learning for fully automated probabilistic evaluation of medical images. Comput. Methods Programs Biomed. 104(3): 75- (2011) - [c17]Matjaz Kukar, Ciril Groselj:
Supporting Diagnostics of Coronary Artery Disease with Neural Networks. ICANNGA (1) 2011: 80-89 - 2010
- [j9]Marko Pozenel, Viljan Mahnic, Matjaz Kukar:
Separating Interleaved HTTP Sessions Using a Stochastic Model. Informatica (Slovenia) 34(2): 199-205 (2010) - [c16]Marko Pozenel, Viljan Mahnic, Matjaz Kukar:
Separation of Interleaved Web Sessions with Heuristic Search. ICDM 2010: 411-420
2000 – 2009
- 2009
- [c15]Matjaz Kukar, Luka Sajn:
Improving Probabilistic Interpretation of Medical Diagnoses with Multi-resolution Image Parameterization: A Case Study. AIME 2009: 136-145 - [c14]Matjaz Kukar, Luka Sajn:
Supporting Diagnostics of Coronary Artery Disease with Multi-resolution Image Parameterization and Data Mining. MIRAGE 2009: 356-367 - 2007
- [j8]Rok Rupnik, Matjaz Kukar, Marjan Krisper:
Integrating Data Mining and Decision Support through Data Mining Based Decision Support System. J. Comput. Inf. Syst. 47(3): 89-104 (2007) - [c13]Matjaz Kukar, Luka Sajn, Ciril Groselj, Jera Groselj:
Multi-resolution Image Parametrization in Stepwise Diagnostics of Coronary Artery Disease. AIME 2007: 119-129 - [c12]Dimitris Tzikas, Matjaz Kukar, Aristidis Likas:
Transductive Reliability Estimation for Kernel Based Classifiers. IDA 2007: 37-47 - 2006
- [j7]Matjaz Kukar:
Quality assessment of individual classifications in machine learning and data mining. Knowl. Inf. Syst. 9(3): 364-384 (2006) - 2005
- [j6]Luka Sajn, Matjaz Kukar, Igor Kononenko, Metka Milcinski:
Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics. Comput. Methods Programs Biomed. 80(1): 47-55 (2005) - [c11]Luka Sajn, Matjaz Kukar, Igor Kononenko, Metka Milcinski:
Automatic Segmentation of Whole-Body Bone Scintigrams as a Preprocessing Step for Computer Assisted Diagnostics. AIME 2005: 363-372 - 2004
- [j5]Matjaz Kukar:
Erratum to "Transductive reliability estimation for medical diagnosis" [Artif. Intell. Med. 29: 81-106(2003)]. Artif. Intell. Medicine 30(2): 199 (2004) - [c10]Matjaz Kukar:
Estimating Confidence Values of Individual Predictions by their Typicalness and Reliability. ECAI 2004: 1045-1046 - [c9]Matjaz Kukar:
Transduction and Typicalness for Quality Assessment of Individual Classifications in Machine Learning and Data Mining. ICDM 2004: 146-153 - 2003
- [j4]Matjaz Kukar:
Transductive reliability estimation for medical diagnosis. Artif. Intell. Medicine 29(1-2): 81-106 (2003) - [c8]Matjaz Kukar:
Drifting Concepts as Hidden Factors in Clinical Studies. AIME 2003: 355-364 - 2002
- [c7]Matjaz Kukar, Ciril Groselj:
Reliable Diagnostics for Coronary Artery Disease. CBMS 2002: 7-12 - [c6]Matjaz Kukar, Igor Kononenko:
Reliable Classifications with Machine Learning. ECML 2002: 219-231 - 2001
- [c5]Matjaz Kukar:
Making Reliable Diagnoses with Machine Learning: A Case Study. AIME 2001: 88-98
1990 – 1999
- 1999
- [j3]Matjaz Kukar, Igor Kononenko, Ciril Groselj, Katarina Kralj, Jure Fettich:
Analysing and improving the diagnosis of ischaemic heart disease with machine learning. Artif. Intell. Medicine 16(1): 25-50 (1999) - [c4]Matjaz Kukar, Ciril Groselj:
Machine Learning in Stepwise Diagnostic Process. AIMDM 1999: 315-325 - 1998
- [j2]Nada Lavrac, Blaz Zupan, Igor Kononenko, Matjaz Kukar, Elpida T. Keravnou:
Intelligent Data Analysis for Medical Diagnosis: Using Machine Learning and Temporal Abstraction. AI Commun. 11(3-4): 191-218 (1998) - [c3]Matjaz Kukar, Igor Kononenko:
Cost-Sensitive Learning with Neural Networks. ECAI 1998: 445-449 - 1997
- [c2]Matjaz Kukar, Ciril Groselj, Igor Kononenko, Jure Fettich:
An Application of Machine Learning in the Diagnosis of Ischaemic Heart Disease. AIME 1997: 461-464 - [c1]Matjaz Kukar, Ciril Groselj, Igor Kononenko, Jure Fettich:
An application of machine learning in the diagnosis of ischaemic heart disease. CBMS 1997: 70-75 - 1996
- [j1]Matjaz Kukar, Igor Kononenko, T. Silvester:
Machine learning in prognosis of the femoral neck fracture recovery. Artif. Intell. Medicine 8(5): 431-451 (1996)
Coauthor Index
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