An all-digital DLL with duty-cycle correction using reusable TDC. - Shao-Ku Kao; Yi-Hsien Hsieh; Hsiang-Chi Cheng (Int. J. Circuit Theory Appl., 2016)

Meta-EHR: A meta-learning approach for electronic health records with a high imbalanced ratio and missing rate. - Hsu-Hsiang Chang; Te-Cheng Hsu; Yi-Hsien Hsieh; Che Lin (EMBC, 2023)

X-RIM: Extreme Recurrent Independent Mechanisms for Noise-resistant and Interpretable Stroke Risk Prediction. - Yi-Hsien Hsieh; Jung-Chi Hsu; Che Lin; Lian-Yu Lin (EMBC, 2023)

Utilizing Graph Neural Networks for Breast Cancer Prognosis Prediction with High-dimensional Genomic Data. - Tzu-Chen Huang; Te-Cheng Hsu; Yi-Hsien Hsieh; Che Lin (EMBC, 2023)

LE-DTA: Local Extrema Convolution for Drug Target Affinity Prediction. - Tanoj Langore; Te-Cheng Hsu; Yi-Hsien Hsieh; Che Lin (ICASSP, 2023)

ReViT: A Hybrid Approach for BCLC Staging of Hepatocellular Carcinoma Using 3D CT with Multiple Instance Learning. - Shun-Cheng Chang; Hsin-Pei Yu; Yi-Hsien Hsieh; Pochuang Wang; Weichung Wang; Tung-Hung Su; Jia-Horng Kao; Che Lin (BHI, 2024)

Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer. - Yun-Chi Chen; Tung Chao; Wimaya Nitya Phandita; Tzu-Yu Sun; Huai-Zhi Wang; Yi-Hsien Hsieh; Le-Yin Hsu; Che Lin (BIBE, 2024)

Deep STI: Deep Stochastic Time-series Imputation on Electronic Health Records. - Ming-Che Cheng; Yi-Hsien Hsieh; Te-Cheng Hsu; Tung-Hung Su; Che Lin (EMBC, 2024)

Scalable Numerical Embeddings for Multivariate Time Series: Enhancing Healthcare Data Representation Learning. - Chun-Kai Huang; Yi-Hsien Hsieh; Ta-Jung Chien; Li-Cheng Chien; Shao-Hua Sun; Tung-Hung Su; Jia-Horng Kao; Che Lin (CoRR, 2024)