Survey study, 2023
Can a computer system predict what type of PMS symptoms a woman will have?
A computer model predicted different PMS types with very high accuracy (over 99%), but only 8 women were tested, so much more research is needed.
What they did
Cross-sectional study using a machine learning method called Gradient Boost Regressor to analyze data from 8 women who completed the Kelly Wallance questionnaire on Google Form. The questionnaire classifies PMS into different types (PMS-A, PMS-C, PMS-D, PMS-H and other symptoms).
What they found
The model predicted different PMS types with very high accuracy: 99.99% for PMS-A, 99.93% for PMS-C, 99.87% for PMS-D, 99.92% for PMS-H, and 99.97% for other symptoms.
What it means for you
A computer system might someday help identify which type of PMS a woman has. This was a very small proof-of-concept study with only 8 women, so it is far too early to use this in real life.
8
Women studied
99.99%
Accuracy for PMS-A prediction
4
Main PMS types classified
About the study
- Original title
- Mathematical modeling of intelligent system for predicting effectiveness of premenstrual syndrome
- Authors
- Ruchi Joshi, Priya Mathur, Amit Gupta et al.
- Journal
- Journal of Interdisciplinary Mathematics
- Year
- 2023
- Study design
- Survey study
- Participants
- 8
- What was tested
- Machine learning model predicting PMS type
- Read the paper
- doi.org/10.47974/jim-1681
Topics
Related studies
Cohort study, 2026
What genetic factors are linked to premenstrual symptoms?
Study, 2026
How do women with PMDD process emotions differently in their brains?
Systematic review, 2026
Why do some women experience mood changes linked to their menstrual cycle?
Case-control study, 2026
Do women with PMS handle emotions differently at different times of the cycle?
Survey study, 2025
Does PMDD or PMS affect quality of life?
Systematic review, 2025
Do people with PMDD and severe PMS have difficulties with emotion regulation?