The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms

The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms

Abstract Hematoporphyrin monomethyl ether-photodynamic therapy (HMME-PDT) is a safe and effective treatment for port-wine stain (PWS). Comprehensive methods for predicting HMME-PDT efficacy based on clinical factors are lacking. This study aims to develop and validate two machine learning models to...

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Bibliographic Details
Main Authors: Hongxia Yan, Yixin Tan, Fan Qiao, Zhuotong Zeng, Yaqian Shi, Xueqin Zhang, Lu Li, Ting Zeng, Yi Zhan, Ruixuan You, Xinglan He, Rong Xiao, Xiangning Qiu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Port-wine stain
HMME-PDT
Machine learning algorithms
Efficacy prediction model
Immediate fluorescence intensity at the lesion site after HMME-PDT
Online Access:https://doi.org/10.1038/s41598-025-06589-3
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https://doi.org/10.1038/s41598-025-06589-3

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