Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images. - Ching-Wei Wang; Cheng-Chang Chang; Yu-Ching Lee; Yi-Jia Lin; Shih-Chang Lo; Po-Chao Hsu; Yi-An Liou; Chih-Hung Wang; Tai-Kuang Chao (Comput. Medical Imaging Graph., 2022)

Detection of ERBB2 and CEN17 signals in fluorescent in situ hybridization and dual in situ hybridization for guiding breast cancer HER2 target therapy. - Ching-Wei Wang; Muhammad Adil Khalil; Yi-Jia Lin; Yu-Ching Lee; Tai-Kuang Chao (Artif. Intell. Medicine, 2023)

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations. - Ching-Wei Wang; Yu-Ching Lee; Yi-Jia Lin; Chun-Chieh Chang; Aung-Kyaw-Oo Sai; Chih-Hung Wang; Tai-Kuang Chao (Comput. Medical Imaging Graph., 2023)

Weakly supervised bilayer convolutional network in segmentation of HER2 related cells to guide HER2 targeted therapies. - Ching-Wei Wang; Kun-Lin Lin; Hikam Muzakky; Yi-Jia Lin; Tai-Kuang Chao (Comput. Medical Imaging Graph., 2023)

Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer. - Ching-Wei Wang; Hikam Muzakky; Nabila Puspita Firdi; Tzu-Chien Liu; Po-Jen Lai; Yu-Chi Wang; Mu-Hsien Yu; Tai-Kuang Chao (npj Digit. Medicine, 2024)

Transformer Deep Learning to Detect Microsatellite Instability Using Histopathological Slides to Guide Colorectal and Endometrial Cancer Immunotherapy. - Ching-Wei Wang; Tai-Kuang Chao (ACPR (1), 2025)

Deep learning to identify aggressive endometrial cancer and predict tumor mutational burden from histopathology slide. - Ching-Wei Wang; Po-Jen Lai; Hikam Muzakky; Tzu-Chiao Chu; Yu-Chi Wang; Mu-Hsien Yu; Chia-Hua Wu; Tai-Kuang Chao (Biomed. Signal Process. Control., 2025)

Interpretable multi-stage attention network to predict cancer subtype, microsatellite instability, TP53 mutation and TMB of endometrial and colorectal cancer. - Ching-Wei Wang; Hikam Muzakky; Yu-Ching Lee; Yu-Pang Chung; Yu-Chi Wang; Mu-Hsien Yu; Chia-Hua Wu; Tai-Kuang Chao (Comput. Medical Imaging Graph., 2025)

ATEC23 Challenge: Automated prediction of treatment effectiveness in ovarian cancer using histopathological images. - Ching-Wei Wang; Nabila Puspita Firdi; Tzu-Chiao Chu; Mohammad Faiz Iqbal Faiz; Mohammad Zafar Iqbal; Yifan Li; Bo Yang; Mayur Mallya; Ali Bashashati; Fei Li; Haipeng Wang; Mengkang Lu; et al. (Medical Image Anal., 2025)

Ensemble transformer-based multiple instance learning to predict pathological subtypes and tumor mutational burden from histopathological whole slide images of endometrial and colorectal cancer. - Ching-Wei Wang; Tzu-Chien Liu; Po-Jen Lai; Hikam Muzakky; Yu-Chi Wang; Mu-Hsien Yu; Chia-Hua Wu; Tai-Kuang Chao (Medical Image Anal., 2025)

Interpretable multi-scale deep learning to detect malignancy in cell blocks and cytological smears of pleural effusion and identify aggressive endometrial cancer. - Ching-Wei Wang; Hikam Muzakky; Yu-Pang Chung; Po-Jen Lai; Tai-Kuang Chao (Medical Image Anal., 2025)

Automated Quantification of HER2 Amplification Levels Using Deep Learning. - Ching-Wei Wang; Kai-Lin Chu; Ting-Sheng Su; Keng-Wei Liu; Yi-Jia Lin; Tai-Kuang Chao (IEEE J. Biomed. Health Informatics, 2025)