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Matjaz Kukar

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2010 – today

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2015
[j13]
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Boris Petelin, Igor Kononenko, Vlado Malacic, Matjaz Kukar:
Dynamic fuzzy paths and cycles in multi-level directed graphs. Eng. Appl. of AI 37: 194-206 (2015)
[c20]
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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]
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  - conf/caise/SubeljBKB14
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Lovro Subelj, Zoran Bosnic, Matjaz Kukar, Marko Bajec:
Automatization of the Stream Mining Process. CAiSE 2014: 409-423
2013
[j12]
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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)
[j11]
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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]
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Anze Pecar, Miha Zidar, Matjaz Kukar:
Reservoir sampling techniques in modern data analysis. BCI 2012: 247-250
2011
[j10]
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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. Artificial Intelligence in Medicine 52(2): 77-90 (2011)
[j9]
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Luka Sajn, Matjaz Kukar:
Image processing and machine learning for fully automated probabilistic evaluation of medical images. Computer Methods and Programs in Biomedicine 104(3): 75- (2011)
[c17]
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Matjaz Kukar, Ciril Groselj:
Supporting Diagnostics of Coronary Artery Disease with Neural Networks. ICANNGA (1) 2011: 80-89
2010
[j8]
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Marko Pozenel, Viljan Mahnic, Matjaz Kukar:
Separating Interleaved HTTP Sessions Using a Stochastic Model. Informatica (Slovenia) 34(2): 199-205 (2010)
[c16]
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Marko Pozenel, Viljan Mahnic, Matjaz Kukar:
Separation of Interleaved Web Sessions with Heuristic Search. ICDM 2010: 411-420

2000 – 2009

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2009
[c15]
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Matjaz Kukar, Luka Sajn:
Improving Probabilistic Interpretation of Medical Diagnoses with Multi-resolution Image Parameterization: A Case Study. AIME 2009: 136-145
[c14]
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Matjaz Kukar, Luka Sajn:
Supporting Diagnostics of Coronary Artery Disease with Multi-resolution Image Parameterization and Data Mining. MIRAGE 2009: 356-367
2007
[c13]
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Matjaz Kukar, Luka Sajn, Ciril Groselj, Jera Groselj:
Multi-resolution Image Parametrization in Stepwise Diagnostics of Coronary Artery Disease. AIME 2007: 119-129
[c12]
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  - conf/ida/TzikasKL07
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Dimitris Tzikas, Matjaz Kukar, Aristidis Likas:
Transductive Reliability Estimation for Kernel Based Classifiers. IDA 2007: 37-47
2006
[j7]
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  - journals/kais/Kukar06
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Matjaz Kukar:
Quality assessment of individual classifications in machine learning and data mining. Knowl. Inf. Syst. 9(3): 364-384 (2006)
2005
[j6]
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Luka Sajn, Matjaz Kukar, Igor Kononenko, Metka Milcinski:
Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics. Computer Methods and Programs in Biomedicine 80(1): 47-55 (2005)
[c11]
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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]
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Matjaz Kukar:
Erratum to "Transductive reliability estimation for medical diagnosis" [Artif. Intell. Med. 29: 81-106(2003)]. Artificial Intelligence in Medicine 30(2): 199 (2004)
[c10]
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Matjaz Kukar:
Estimating Confidence Values of Individual Predictions by their Typicalness and Reliability. ECAI 2004: 1045-1046
[c9]
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Matjaz Kukar:
Transduction and Typicalness for Quality Assessment of Individual Classifications in Machine Learning and Data Mining. ICDM 2004: 146-153
2003
[j4]
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Matjaz Kukar:
Transductive reliability estimation for medical diagnosis. Artificial Intelligence in Medicine 29(1-2): 81-106 (2003)
[c8]
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Matjaz Kukar:
Drifting Concepts as Hidden Factors in Clinical Studies. AIME 2003: 355-364
2002
[c7]
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Matjaz Kukar, Ciril Groselj:
Reliable Diagnostics for Coronary Artery Disease. CBMS 2002: 7-12
[c6]
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Matjaz Kukar, Igor Kononenko:
Reliable Classifications with Machine Learning. ECML 2002: 219-231
2001
[c5]
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Matjaz Kukar:
Making Reliable Diagnoses with Machine Learning: A Case Study. AIME 2001: 88-98

1990 – 1999

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1999
[j3]
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Matjaz Kukar, Igor Kononenko, Ciril Groselj, Katarina Kralj, Jure Fettich:
Analysing and improving the diagnosis of ischaemic heart disease with machine learning. Artificial Intelligence in Medicine 16(1): 25-50 (1999)
[c4]
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Matjaz Kukar, Ciril Groselj:
Machine Learning in Stepwise Diagnostic Process. AIMDM 1999: 315-325
1998
[j2]
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  - journals/aicom/LavracZKKK98
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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]
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Matjaz Kukar, Igor Kononenko:
Cost-Sensitive Learning with Neural Networks. ECAI 1998: 445-449
1997
[c2]
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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]
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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]
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Matjaz Kukar, Igor Kononenko, T. Silvester:
Machine learning in prognosis of the femoral neck fracture recovery. Artificial Intelligence in Medicine 8(5): 431-451 (1996)

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