This study proposes an unsupervised learning framework that integrates the few-shot learning for analyzing dental panoramic radiographs. The framework is specifically designed to address...
We have developed a customized SEA population-specific reference panel consisting of 2550 samples via cross-panel imputation that resulted in 113,851,450 variants. Our reference panel...
Experimental configurationThe configuration environment for this study was a Windows 11 workstation with an AMD Ryzen 7 5800H processor and Radeon Graphics (3.20Â GHz). It...