Machine Learning and Artificial Intelligence Technologies to Predict Premenstrual Syndrome
Chapter from the book:
Aydın Doğan,
R.
&
Hüseyinoğlu,
S.
(eds.)
2024.
Current Research on Midwifery and Women's Health.
Synopsis
Premenstrual syndrome (PMS) is a syndrome accompanied by physical and mental symptoms that occurs in the luteal phase of the menstrual cycle and significantly affects women's daily lives. Symptoms include bloating, headaches, fatigue, emotional fluctuations and irritability, which can significantly affect daily life for some women. In recent years, innovative solutions have been offered for predicting and managing PMS with machine learning and artificial intelligence technologies. These technologies can be used to predict the likelihood of PMS symptoms occurring by analyzing large data sets. The data often includes factors such as personal health records, information from menstrual cycle tracking apps, hormone levels, lifestyle factors and psychological assessments. With machine learning, PMS symptoms are predicted, enabling women to cope with these symptoms more effectively and allowing healthcare professionals to create personalized treatment plans.
How to cite this book
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Published
DOI
Categories
Copyright (c) 2024 Reyhan Aydın Doğan, Sebahat Hüseyinoğlu; Berru Sena Beşevli, Sebahat Hüseyinoğlu, Bilgenur Bulut, Ceyda Eker, Reyhan Aydın Doğan, Nurbanu Güven, Roza Narzullayeva, Şeyma Nur Yılmaz, Yasemin Ersoy, Zübeyde Ceylan, İlkay Buran, Mehmet Özdemir, Rabia Görücü, Kübra Şengör, Sibel Karakoç, Neriman Güdücü, Begüm Can