249 citations · 444 across the 4 of their papers we have counts for
4 papers
Meta-Imputation Balanced (MIB): An Ensemble Approach for Handling Missing Data in Biomedical Machine Learning
Fatemeh Azad, Zoran Bosnić, Matjaž Kukar
Missing data represents a fundamental challenge in machine learning applications, often reducing model performance and reliability. This problem is particularly acute in fields lik…
Differentiating Viral and Bacterial Infections: A Machine Learning Model Based on Routine Blood Test Values
Gregor Gunčar, Matjaž Kukar, Tim Smole +9
The growing threat of antibiotic resistance necessitates accurate differentiation between bacterial and viral infections for proper antibiotic administration. In this study, a Viru…
COVID-19 diagnosis by routine blood tests using machine learning
Matjaž Kukar, Gregor Gunčar, Tomaž Vovko +7
Physicians taking care of patients with coronavirus disease (COVID-19) have described different changes in routine blood parameters. However, these changes, hinder them from perfor…
Application of machine learning for hematological diagnosis
Gregor Gunčar, Matjaž Kukar, Mateja Notar +4
Quick and accurate medical diagnosis is crucial for the successful treatment of a disease. Using machine learning algorithms, we have built two models to predict a hematologic dise…