Skin aging classification

deep learning-driven intelligent skin aging classification method improves skin aging classification in silico (87.66% accuracy, 88.27% precision, 87.66% recall, 87.80% F1, 97.94% specificity).

“the proposed method achieves an accuracy of 87.66%, a precision of 88.27%, a recall of 87.66%, an F1 score of 87.80%, and a specificity of 97.94%”

In silicoskin

Deep learning-driven high-frequency ultrasound method for skin aging assessment

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·25 Jun 2026