M. Kukar

发表

Machine learning improves the accuracy of coronary artery disease diagnostic methods

I. Kononenko, C. Groselj, M. Kukar, 1997, Computers in Cardiology 1997.

Machine Learning and Data Mining: Introduction to Principles and Algorithms

Igor Kononenko, Matjaz Kukar, I. Kononenko, 2007 .

Prognosing the Survival Time of Patients with Anaplastic Thyroid Carcinoma using Machine Learning

I. Kononenko, M. Robnik-Sikonja, M. Kukar, 1997 .

Application of machine learning for hematological diagnosis

Matjaž Kukar, Miran Brvar, Mateja Notar, 2017 .

Diagnosing brain tumours by routine blood tests using machine learning

M. Kukar, G. Guncar, Mateja Notar, 2019, Scientific Reports.

Machine learning in blood group determination of Danish Jersey cattle

M. Kukar, 1998 .

Prognosing the femoral neck fracture recovery with machine learning

I. Kononenko, M. Kukar, T. Silvester, 1998 .

Diagnosing the Ischaemic Heart Disease with Machine Learning

I. Kononenko, C. Groselj, M. Kukar, 1998 .

EXPLANATION AND RELIABILITY OF INDIVIDUAL PREDICTIONS : RECENT RESEARCH BY LKM

I. Kononenko, M. Robnik-Sikonja, E. Štrumbelj, 2012 .

Machine Learning and Data Mining: Introduction to Principles and Algorithms

Igor Kononenko, Matjaž Kukar, I. Kononenko, 2007 .

Image processing and machine learning for fully automated probabilistic evaluation of medical images

Matjaz Kukar, Luka Sajn, M. Kukar, 2011, Comput. Methods Programs Biomed..

Analysing and improving the diagnosis of ischaemic heart disease with machine learning

Igor Kononenko, Matjaz Kukar, Ciril Groselj, 1999, Artif. Intell. Medicine.

Transductive Reliability Estimation for Individual Classifications in Machine Learning and Data Mining

Matjaž Kukar, M. Kukar, 2012 .

Quality assessment of individual classifications in machine learning and data mining

Matjaz Kukar, M. Kukar, 2006, Knowledge and Information Systems.

Intelligent Data Analysis for Medical Diagnosis: Using Machine Learning and Temporal Abstraction

Elpida T. Keravnou, Nada Lavrac, Blaz Zupan, 1998, AI Commun..

Experiments with Machine Learning in the Prediction of Coronary Artery Disease Progression

Igor Kononenko, Andrej Dobnikar, Matjaž Kukar, 1997 .

Machine learning in prognosis of the femoral neck fracture recovery

Igor Kononenko, Matjaz Kukar, T. Silvester, 1996, Artif. Intell. Medicine.

COVID-19 diagnosis by routine blood tests using machine learning pdf

Matjaz Kukar, Gregor Guncar, Tomaz Vovko, 2020, Scientific Reports.

Transductive reliability estimation for medical diagnosis

Matjaz Kukar, M. Kukar, 2003, Artif. Intell. Medicine.

AgroDSS: A decision support system for agriculture and farming

Darko Pevec, Matjaz Kukar, Rok Rupnik, 2019, Comput. Electron. Agric..

Transductive Machine Learning for Reliable Medical Diagnostics

Ciril Grošelj, Matjaž Kukar, C. Groselj, 2005, Journal of Medical Systems.

Transduction and typicalness for quality assessment of individual classifications in machine learning and data mining

Matjaz Kukar, M. Kukar, 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study

M. Kukar, Nina Ružić Gorenjec, C. Grašič Kuhar, 2020, JMIR mHealth and uHealth.

An application of machine learning to haematological diagnosis

Matjaž Kukar, Miran Brvar, Mateja Notar, 2017, Scientific Reports.

An application of machine learning to haematological diagnosis

M. Kukar, Mateja Notar, M. Brvar, 2017, Scientific Reports.

Modern parameterization and explanation techniques in diagnostic decision support system: A case study in diagnostics of coronary artery disease

Igor Kononenko, Matjaz Kukar, Ciril Groselj, 2011, Artif. Intell. Medicine.

Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics

Igor Kononenko, Matjaz Kukar, Luka Sajn, 2005, Comput. Methods Programs Biomed..

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study (Preprint)

M. Kukar, Nina Ružić Gorenjec, C. Grašič Kuhar, 2019 .

Cost-Sensitive Learning with Neural Networks

Igor Kononenko, Matjaz Kukar, I. Kononenko, 1998, ECAI.

Disease Progression of Hypertrophic Cardiomyopathy: Modeling Using Machine Learning

D. Fotiadis, G. MacGowan, Z. Bosnić, 2022, JMIR medical informatics.

An application of machine learning in the diagnosis of ischaemic heart disease

Igor Kononenko, Matjaz Kukar, Ciril Groselj, 1997, Proceedings of Computer Based Medical Systems.

Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study

M. Kukar, Nina Ružić Gorenjec, C. Grašič Kuhar, 2020, JMIR mHealth and uHealth.

Explanation and Reliability of Individual Predictions

Erik Strumbelj, Marko Robnik-Sikonja, Darko Pevec, 2013, Informatica.

A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy

Marko Robnik-Šikonja, Dimitrios I Fotiadis, Matjaž Kukar, 2021, Comput. Biol. Medicine.

Disease Progression of Hypertrophic Cardiomyopathy: Modeling Using Machine Learning (Preprint)

D. Fotiadis, G. MacGowan, Z. Bosnić, 2021 .

A topological approach to delineation and arrhythmic beats detection in unprocessed long-term ECG signals

Jana Faganeli Pucer, Matjaz Kukar, M. Kukar, 2018, Comput. Methods Programs Biomed..

Differentiating viral and bacterial infections: A machine learning model based on routine blood test values

M. Kukar, Mateja Notar, M. Brvar, 2023, Heliyon.

Drifting Concepts as Hidden Factors in Clinical Studies

Matjaz Kukar, M. Kukar, 2003, AIME.

Frequent subgraph mining in oceanographic multi-level directed graphs

Igor Kononenko, Boris Petelin, Matjaž Kukar, 2019, Int. J. Geogr. Inf. Sci..

Multi-level association rules and directed graphs for spatial data analysis

Igor Kononenko, Matjaz Kukar, Boris Petelin, 2013, Expert Syst. Appl..

Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics

I. Kononenko, M. Kukar, L. Sajn, 2005, Comput. Methods Programs Biomed..

Automatic Segmentation of Whole-Body Bone Scintigrams as a Preprocessing Step for Computer Assisted Diagnostics

Igor Kononenko, Matjaz Kukar, Luka Sajn, 2005, AIME.

Transductive Reliability Estimation for Kernel Based Classifiers

Aristidis Likas, Dimitris Tzikas, Matjaz Kukar, 2007, IDA.

Evaluation of prediction reliability in regression using the transduction principle

Z. Bosnic, I. Kononenko, M. Robnik-Sikonja, 2003, The IEEE Region 8 EUROCON 2003. Computer as a Tool..

Multi-resolution Image Parametrization in Stepwise Diagnostics of Coronary Artery Disease

Matjaz Kukar, Ciril Groselj, Luka Sajn, 2007, AIME.

Supporting Diagnostics of Coronary Artery Disease with Neural Networks

Matjaz Kukar, Ciril Groselj, M. Kukar, 2011, ICANNGA.