Artificial Intelligence in Personalized Healthcare Analysis for Women's' Menstrual Health Disorders

The paper presents an AI-based model which depending on the input of a woman for a finite number of menstrual cycles helps in determining the possible ovulation dates as well as possibility of some health risks e.g., Premenstrual Syndrome, Luteal Phase Defect etc. The architecture of the model consi...

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Bibliographic Details
Published in2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS) Vol. 30; pp. 751 - 760
Main Authors Sosnowski, Lukasz, Zulawinska, Joanna, Dutta, Soma, Szymusik, Iwona, Zygula, Aleksandra, Bambul-Mazurek, Elzbieta
Format Conference Proceeding Journal Article
LanguageEnglish
Published Polish Information Processing Society 01.01.2022
Subjects
Analytical models
Detectors
Machine learning
Precision medicine
Protocols
Standardization
User interfaces
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ISSN2300-5963
DOI10.15439/2022F59

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Summary:The paper presents an AI-based model which depending on the input of a woman for a finite number of menstrual cycles helps in determining the possible ovulation dates as well as possibility of some health risks e.g., Premenstrual Syndrome, Luteal Phase Defect etc. The architecture of the model consists of three layers, namely analyzing and detecting the features from a single cycle, analyzing cycle level concepts based on the analyzed features, and analyzing the user's health risks based on the cycle level concepts accumulated over a finitely many cycles.
ISSN:2300-5963
DOI:10.15439/2022F59