A lossless data reduction technique for wireless EEG recorders and its use in selective data filtering for seizure monitoring. - Chengliang Dai; Christopher Bailey 002 (EMBC, 2015)

Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records. - Jingqing Zhang; Xiaoyu Zhang 008; Kai Sun 005; Xian Yang 001; Chengliang Dai; Yike Guo (BIBM, 2019)

Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification. - Xiaoyu Zhang 008; Jingqing Zhang; Kai Sun 005; Xian Yang 001; Chengliang Dai; Yike Guo (BIBM, 2019)

Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction. - Shuo Wang 011; Chengliang Dai; Yuanhan Mo; Elsa D. Angelini; Yike Guo; Wenjia Bai (BrainLes@MICCAI (2), 2019)

Transfer Learning from Partial Annotations for Whole Brain Segmentation. - Chengliang Dai; Yuanhan Mo; Elsa D. Angelini; Yike Guo; Wenjia Bai (DART/MIL3ID@MICCAI, 2019)

A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit. - Christopher Crispin-Bailey; Chengliang Dai; Jim Austin (IEEE Trans. Biomed. Circuits Syst., 2019)

Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction. - Chengliang Dai; Shuo Wang 011; Hadrien Raynaud; Yuanhan Mo; Elsa D. Angelini; Yike Guo; Wenjia Bai (BrainLes@MICCAI (1), 2020)

Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling. - Chengliang Dai; Shuo Wang 011; Yuanhan Mo; Kaichen Zhou; Elsa D. Angelini; Yike Guo; Wenjia Bai (MICCAI (4), 2020)

Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation. - Shuo Wang 011; Giacomo Tarroni; Chen Qin; Yuanhan Mo; Chengliang Dai; Chen Chen 042; Ben Glocker; Yike Guo; Daniel Rueckert; Wenjia Bai (MICCAI (4), 2020)

Efficient Deep Representation Learning by Adaptive Latent Space Sampling. - Yuanhan Mo; Shuo Wang 011; Chengliang Dai; Rui Zhou; Zhongzhao Teng; Wenjia Bai; Yike Guo (CoRR, 2020)

Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling. - Chengliang Dai; Shuo Wang 011; Yuanhan Mo; Elsa D. Angelini; Yike Guo; Wenjia Bai (CoRR, 2020)

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. - Raghav Mehta; Angelos Filos; Ujjwal Baid; Chiharu Sako; Richard McKinley; Michael Rebsamen; Katrin Dätwyler; Raphael Meier; Piotr Radojewski; Gowtham Krishnan Murugesan; Sahil S. Nalawade; Chandan Ganesh; et al. (CoRR, 2021)

The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion). - Shuo Wang 011; Chen Qin; Chengyan Wang; Kang Wang 004; Haoran Wang 009; Chen Chen 042; Cheng Ouyang; Xutong Kuang; Chengliang Dai; Yuanhan Mo; Zhang Shi; Chenchen Dai; et al. (CoRR, 2022)

Suggestive annotation of brain MR images with gradient-guided sampling. - Chengliang Dai; Shuo Wang 011; Yuanhan Mo; Elsa D. Angelini; Yike Guo; Wenjia Bai (Medical Image Anal., 2022)

A hybrid framework with large language models for rare disease phenotyping. - Jinge Wu; Hang Dong 002; Zexi Li; Haowei Wang; Runci Li; Arijit Patra; Chengliang Dai; Waqar Ali; Phil Scordis; Honghan Wu (BMC Medical Informatics Decis. Mak., 2024)

Understanding Dataset Bias in Medical Imaging: A Case Study on Chest X-rays. - Ethan Dack; Chengliang Dai (CoRR, 2025)

Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge. - Kang Wang 004; Chen Qin; Zhang Shi; Haoran Wang 009; Xiwen Zhang; Chen Chen 042; Cheng Ouyang; Chengliang Dai; Yuanhan Mo; Chenchen Dai; Xutong Kuang; Ruizhe Li; et al. (CoRR, 2025)