Trustworthy artificial intelligence for personalized healthcare decision making: development of open and safe measures, models and methods

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Journal Title
Journal ISSN
Volume Title
School of Science | A4 Artikkeli konferenssijulkaisussa
Date
2021
Major/Subject
Mcode
Degree programme
Language
en
Pages
1
Series
Abstract
Our DIHEML research project develops open and safe measures, models and methods that can support personalized healthcare decision making with trustworthy artificial intelligence addressing carefully patient's rights and data privacy regulation. With our new methodology statistically significant rating differences of questionnaire answers can be linked to machine learning results thus enabling to develop better machine learning for well-personalized care.
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Keywords
personalized healthcare decision making, artificial intelligence, machine learning, patient’s rights, ethics, healthcare guidelines, open access data, trustworthy, interpretable
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Citation
Lahti, Lauri. 2021. Trustworthy artificial intelligence for personalized healthcare decision making: development of open and safe measures, models and methods. Proceedings of the 7th International Symposium ICF Education, 23-24 October 2021. 1.