Machine Learning for Medical Imaging Diagnosis: A Comprehensive Framework for Ukrainian Healthcare Implementation

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Authors: Oleh Ivchenko, Dmytro Grybeniuk, Iryna Ivchenko
Cited by: 0

Abstract

This comprehensive paper synthesizes research on implementing machine learning systems for medical imaging diagnosis in Ukrainian healthcare settings. Drawing from 22 detailed studies covering global best practices, technical architectures, clinical integration protocols, and Ukrainian-specific adaptations, we present a complete framework for deploying AI-powered diagnostic systems. The framework addresses CNN and transformer architectures, explainable AI, federated learning, PACS integration, radiologist collaboration protocols, Ukrainian infrastructure assessment, language localization, regulatory compliance, and the ScanLab reference implementation.Authors: Ivchenko, Oleg (IT company Lohika, Capgemini Engineering, Odessa National Polytechnic University, Department of Economic Cybernetics and Information Technologies) Researcher Dmytro Grybeniuk, Dmytro Grybeniuk (Irvine Valley College, Odessa National Polytechnic University) Research group Ivchenko, Iryna (Odessa National Polytechnic University) Research group

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education AI in cancer detection COVID-19 diagnosis using AI

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 February 2026
Language
EN