Development of a Machine Learning Model for Predicting Herbal Medicine Treatment Response in Chronic Dizziness Patients
Journal · Frontiers in Neurology (2025)
Original authors · Kim GH, Cho SY, Park JK, et al.
DOI · 10.3389/fneur.2025.1389234
Summary
A machine learning model for predicting treatment response was developed using data from 420 chronic dizziness patients receiving herbal medicine treatment. The Random Forest model showed the highest predictive power with AUC 0.84.
Key figures
Analysis Subjects
420 subjects
Prediction Accuracy
AUC 0.84
Predictive Variables
12 variables
Conclusion
Machine learning-based predictive models can be utilized for prior evaluation of herbal medicine treatment responsiveness in chronic dizziness.
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Findings were observed under specific study conditions and results may differ by individual. This does not replace medical consultation.