Differentiating Viral and Bacterial Infections: A Machine Learning Model Based on Routine Blood Test Values

no code implementations • 13 May 2023 • Gregor Gunčar, Matjaž Kukar, Tim Smole, Sašo Moškon, Tomaž Vovko, Simon Podnar, Peter Černelč, Miran Brvar, Mateja Notar, Manca Köster, Marjeta Tušek Jelenc, Marko Notar

In this study, a Virus vs. Bacteria machine learning model was developed to distinguish between these infection types using 16 routine blood test results, C-reactive protein concentration (CRP), biological sex, and age.

Decision Making Management +1

COVID-19 diagnosis by routine blood tests using machine learning

no code implementations • 4 Jun 2020 • Matjaž Kukar, Gregor Gunčar, Tomaž Vovko, Simon Podnar, Peter Černelč, Miran Brvar, Mateja Zalaznik, Mateja Notar, Sašo Moškon, Marko Notar

The model was based and cross-validated on the routine blood tests of 5, 333 patients with various bacterial and viral infections, and 160 COVID-19-positive patients.

BIG-bench Machine Learning COVID-19 Diagnosis +2

Application of machine learning for hematological diagnosis

no code implementations • 1 Aug 2017 • Gregor Gunčar, Matjaž Kukar, Mateja Notar, Miran Brvar, Peter Černelč, Manca Notar, Marko Notar

Quick and accurate medical diagnosis is crucial for the successful treatment of a disease.

BIG-bench Machine Learning Medical Diagnosis