<b> A deep learning-based Parkinson's disease classification using fused images</b>

The Pyramid channel-based feature attention network (PCFAN) chooses the critical features. The efficiency of the approaches is tested using the PPMI and NTUA datasets. Our proposed approach obtains 99.34% accuracy, 98.53% sensitivity, 97.78% specificity, and 99.12% F-Score compared to previous methods.

基于金字塔通道的特征注意力网络（Pyramid channel-based feature attention network，PCFAN）能够筛选关键特征。本研究所提方法的有效性通过PPMI与NTUA数据集进行验证。相较于此前已有方法，本方法可达到99.34%的准确率、98.53%的灵敏度、97.78%的特异度以及99.12%的F测度。