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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
Abstract
ML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness which is a concept that includes fairness, data security, ethics, privacy, and the ability to explain model decisions, either post-hoc or during the development. One of the interesting examples of a medical applications is automatic SVD diagnostics. A complete diagnosis of this disease requires a fusion of results for different lesions. This paper presents preliminary results related to the automatic recognition of SVD, more specifically the detection of CMB and WMH. The results achieved are presented in the context of trustworthy AI-based systems.
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Authors (7)
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Julia Niemierko mgr
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Małgorzata Grzywińska mgr
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Edyta Szurowska prof. dr hab.
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-031-16159-9_1
- License
- Copyright (2023 The Author(s), under exclusive license to Springer Nature Switzerland AG)
Keywords
Details
- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Ferlin M., Klawikowska Z., Niemierko J., Grzywińska M., Kwasigroch A., Szurowska E., Grochowski M.: Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.// Intelligent and Safe Computer Systems in Control and Diagnostics/ : , , s.3-16
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-031-16159-9_1
- Verified by:
- Gdańsk University of Technology
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