Study, 2012
Can a computer algorithm help diagnose PMS more accurately?
Researchers developed a computer algorithm to help diagnose borderline PMS cases by identifying the most important symptoms. The study focused on building the algorithm but did not test how well it diagnoses PMS cases in practice.
What they did
Researchers selected 10 PMS symptoms based on medical guidelines. They processed these symptoms using mathematical methods for 50 cases labeled as borderline or not borderline. They created a decision tree to identify the most important symptom patterns for classification.
What they found
The researchers created a decision tree using information from the symptoms to identify important patterns. The method selected the best combinations of symptoms to classify PMS cases. The approach used mathematical logic to measure how closely borderline cases matched PMS symptom patterns.
What it means for you
A computer algorithm might help diagnose borderline PMS cases by identifying the most important symptoms. The main limitation is that the work focused on building the algorithm rather than testing whether it actually diagnoses PMS cases accurately in practice.
50
cases analyzed
10
PMS symptoms used in the algorithm
About the study
- Original title
- A novel mathematical approach to diagnose premenstrual syndrome
- Authors
- Chattopadhyay S, Acharya UR
- Journal
- Journal of medical systems
- Year
- 2012
- Study design
- Study
- Participants
- 50
- What was tested
- None; methodological study
- Read the paper
- doi.org/10.1007/s10916-011-9683-4