Кафедра штучного інтелекту (ШІ)

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https://ela.kpi.ua/handle/123456789/52504

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Перегляд Кафедра штучного інтелекту (ШІ) за Автор "Damaskina, Olena Ihorivna"

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    Platform for Medical Data Processing and Treatment Plan Management
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Damaskina, Olena Ihorivna; Sineglazov, Viktor Mykhailovych
    Master’s thesis: 122 pages, 2 figures, 2 tables, 70 references, 2 appendices. The object of research is the processes of medical data processing, integration, and management in modern healthcare information systems using artificial intelligence technologies. The subject of research is architectural, algorithmic, and software methods for developing medical platforms for medical data processing, medical image analysis, treatment plan formation and management, as well as quality assurance and validation of AI components. The purpose of the research is to develop and study a platform for medical data processing and treatment plan management with integrated artificial intelligence and Explainable AI modules, ensuring reliability, interpretability of results, and data quality control. The relevance of the research is driven by the rapid digital transformation of healthcare and the increasing volume of medical data, particularly medical images, which require automated, reliable, and interpretable processing. At the same time, significant challenges remain related to data integration, data quality, AI result validation, and compliance with regulatory requirements. The scientific novelty of the research consists in: (1) a systematic approach to the design of a medical platform covering the full medical data lifecycle; (2) integration of AI-based medical image analysis with Explainable AI mechanisms to improve transparency and trust in the results; (3) formalization of quality control and validation points at different levels of the system architecture. The practical value of the research lies in the developed prototype of a medical platform that can be used for medical data processing, ophthalmological image analysis, and support of treatment plan management processes. The proposed architecture provides modularity, scalability, compliance with medical data standards, and the ability to integrate with existing healthcare information systems.