Hybrid Classifiers Based on CNN, LSOF, GMDH in COVID-19 Pneumonic Lesions Types Classification Task. - Oleksandr Davydko; Yaroslav Hladkyi; Mykola Linnik; Olena Nosovets; Vladimir Pavlov; Ievgen Nastenko (CSIT (1), 2021)

Class-Oriented Features Selection Technology in Medical Images Classification Problem on the Example of Distinguishing Between Tuberculosis Sensitive and Resistant Forms. - Oleksandr Matviichuk; Olena Nosovets; Mykola Linnik; Oleksandr Davydko; Vladimir Pavlov; Ievgen Nastenko (CSIT (1), 2021)

A Pipeline for the Diagnosis and Classification of Lung Lesions for Patients with COVID-19. - Oleksandr Davydko; Olena Horodetska; Ievgen Nastenko; Yaroslav Hladkyi; Vladimir Pavlov; Luca Longo; Mykola Linnik; Oleksandr Galkin (CSIT, 2022)

Lung images Classification with Textural Characteristics and Hybrid Classification Schemes. - Oleksandr Davydko (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2023)

Selecting Textural Characteristics of Chest X-Rays for Pneumonia Lesions Classification with the Integrated Gradients XAI Attribution Method. - Oleksandr Davydko; Vladimir Pavlov; Luca Longo (xAI (1), 2023)

Assesing the Interpretability of the Statistical Radiomic Features via Image Saliency Maps in Medical Image Classification Tasks. - Oleksandr Davydko (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps. - Oleksandr Davydko; Vladimir Pavlov; Przemyslaw Biecek; Luca Longo (xAI (4), 2024)