Prediction of Therapeutic Outcomes of Female Pattern Hair Loss Patients Based on Clinical Features with Application of Artificial Intelligence
December 2021
in “
Journal of The American Academy of Dermatology
”
TLDR Artificial intelligence can accurately predict hair growth and treatment results in female pattern hair loss patients, with age of onset and duration being key factors.
This study developed machine learning models to predict therapeutic outcomes in female pattern hair loss (FPHL) patients. The researchers collected data from 591 FPHL patients and used XGBoost and CatBoost algorithms to train the models. The models accurately predicted changes in hair density and hair caliber at different follow-up times. The age of onset and FPHL duration were found to be the most influential factors in the prediction models. This study highlights the potential of machine learning in predicting hair growth and tailoring treatment for FPHL patients.
