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Matjaz Kukar
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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
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
Frequent subgraph mining in oceanographic multi-level directed graphs. Int. J. Geogr. Inf. Sci. 33(10): 1936-1959 (2019) - 2018
- [j15]Jana Faganeli Pucer
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
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
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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