š° Cost-Benefit Analysis of Medical AI Implementation for Ukrainian Hospitals Author: Oleh Ivchenko, PhD Candidate Cost-benefit analysis of AI implementation for Ukrainian hospitals Affiliations: Odessa National Polytechnic University (ONPU) | Stabilarity Hub Series: Machine Learning for Medical Diagnosis in Ukraine ā Article 29 of 35 Date: February 2026 Abstract The adoption of artificial intelligence in…
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[Medical ML] PACS Integration Strategies for AI-Powered Medical Imaging: A Comprehensive Framework
# PACS Integration Strategies for AI-Powered Medical Imaging: A Comprehensive Framework for Clinical Deployment **Author:** Oleh Ivchenko, PhD Candidate **Affiliation:** Odessa National Polytechnic University (ONPU) | Stabilarity Hub **Series:** Medical ML for Diagnosis ā Article 19 of 35 **Date:** February 9, 2026 **Category:** Clinical Workflow Integration — ## Abstract The integration of artificial intelligence (AI)…
[Medical ML] Federated Learning for Privacy-Preserving Medical AI Training: Multi-Institutional Collaboration Without Data Sharing
š Academic Citation: Ivchenko, O. (2026). Federated Learning for Privacy-Preserving Medical AI Training: Multi-Institutional Collaboration Without Data Sharing. Medical ML for Diagnosis Series. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18685263 Abstract Federated learning (FL) represents a paradigm shift in collaborative machine learning that enables multiple healthcare institutions to jointly train diagnostic AI models without sharing sensitive…
[Medical ML] Transfer Learning and Domain Adaptation: Bridging the Data Gap in Medical Imaging AI
š Academic Citation: Ivchenko, O. (2026). Transfer Learning and Domain Adaptation: Bridging the Data Gap in Medical Imaging AI. Medical ML Diagnosis Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18672185 Abstract The remarkable success of deep learning in medical imaging has been tempered by a fundamental challenge: the scarcity of large-scale, annotated medical datasets essential for…
[Medical ML] Explainable AI (XAI) for Clinical Trust: Bridging the Black Box Gap
š Academic Citation: Ivchenko, O. (2026). Explainable AI (XAI) for Clinical Trust: Bridging the Black Box Gap in Medical Imaging Diagnostics. Medical ML Research Series. Odesa National Polytechnic University. Abstract The deployment of deep learning models in clinical radiology has achieved remarkable diagnostic accuracy, often matching or exceeding human expert performance. However, these models remain…
[Medical ML] Hybrid Models: Best of Both Worlds ā CNN-Transformer Architectures for Clinical Imaging
š Academic Citation: Ivchenko, O. (2026). [Medical ML] Hybrid Models: Best of Both Worlds ā CNN-Transformer Architectures for Clinical Imaging. Medical Machine Learning for Diagnosis Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18752852 Abstract The convergence of Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) represents a paradigm shift in medical image analysis, addressing the fundamental…
[Medical ML] Vision Transformers in Radiology: Architecture, Applications, and Clinical Performance
š Academic Citation: Oleh Ivchenko. (2026). Vision Transformers in Radiology: Architecture, Applications, and Clinical Performance. Medical ML Diagnosis Series, Article 14. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18672181 Abstract Vision Transformers (ViT) represent a paradigm shift in medical image analysis, applying the revolutionary attention mechanism from natural language processing to radiological imaging. This comprehensive review examines…
[Medical ML] Physician Resistance: Causes and Solutions
š Academic Citation: Ivchenko, O. (2026). Physician Resistance to Healthcare AI: Understanding Causes and Building Collaborative Practice. Medical ML Research Series. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18752854 š¤ Oleh Ivchenko, PhD Candidate šļø Medical AI Research Laboratory, Odessa National Polytechnic University (ONPU) š February 2026 Physician Adoption Technology Acceptance Healthcare AI Implementation Change Management Human-AI…
[Medical ML] Failed Implementations: What Went Wrong
š Academic Citation: Ivchenko, O. (2026). [Medical ML] Failed Implementations: What Went Wrong. Medical Machine Learning for Diagnosis Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18752858 Abstract The healthcare artificial intelligence literature predominantly features success stories, creating a survivorship bias that inadequately prepares implementers for the challenges of real-world deployment. This paper addresses this gap through…
[Medical ML] China’s Massive Medical AI Deployment
š Medical Machine Learning Research Series Chinas massive medical AI deployment and adoption China’s Massive Medical AI Deployment: Scale, Strategy, and Implications for Global Healthcare Transformation š¤ Oleh Ivchenko, PhD Candidate šļø Medical AI Research Laboratory, Odessa National Polytechnic University (ONPU) š February 2026 China Healthcare AI Large-Scale Deployment Digital Health Infrastructure NMPA Regulation Healthcare…