Work

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

Year: 2026

Type: article

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

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.18615147

Authors: Ivchenko, Oleg, Dmytro Grybeniuk, Ivchenko, Iryna

Institutions: Odesа Polytechnic National University, Capgemini (United States), Irvine Valley College

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7128613400

FWCI:

Cites:

Cited by:

Related to: