Risk prediction for cardiovascular disease using ECG data in the China kadoorie biobank. - Yanting Shen; Yang Yang 125; Sarah Parish; Zhengming Chen; Robert Clarke; David A. Clifton (EMBC, 2016)

Does Higher Order LSTM Have Better Accuracy in Chunking and Named Entity Recognition? - Yi Zhang 050; Xu Sun 001; Yang Yang 125 (CoRR, 2017)

Does Higher Order LSTM Have Better Accuracy for Segmenting and Labeling Sequence Data? - Yi Zhang 050; Xu Sun 001; Shuming Ma; Yang Yang 125; Xuancheng Ren (COLING, 2018)

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data. - Yang Yang 125; Katherine E. Niehaus; Timothy M. Walker; Zamin Iqbal; A. Sarah Walker; Daniel J. Wilson 001; Tim E. A. Peto; Derrick W. Crook; E. Grace Smith; Tingting Zhu 001; David A. Clifton (Bioinform., 2018)

Patient-Specific Physiological Monitoring and Prediction Using Structured Gaussian Processes. - Tingting Zhu 001; Glen Wright Colopy; Glenn H. MacEwen; Katherine E. Niehaus; Yang Yang 125; Chris W. Pugh; David A. Clifton (IEEE Access, 2019)

Application of machine learning techniques to tuberculosis drug resistance analysis. - Samaneh Kouchaki; Yang Yang 125; Timothy M. Walker; A. Sarah Walker; Daniel J. Wilson 001; Timothy E. A Peto; Derrick W. Crook; CRyPTIC Consortium; David A. Clifton (Bioinform., 2019)

DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis. - Yang Yang 125; Timothy M. Walker; A. Sarah Walker; Daniel J. Wilson 001; Timothy E. A Peto; Derrick W. Crook; Farah Shamout; CRyPTIC Consortium; Tingting Zhu 001; David A. Clifton (Bioinform., 2019)

An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction. - Yang Yang 125; Timothy M. Walker; Samaneh Kouchaki; Chenyang Wang; Timothy E. A Peto; Derrick W. Crook; David A. Clifton (Briefings Bioinform., 2021)

Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions. - Fenglin Liu; Bang Yang; Chenyu You; Xian Wu 001; Shen Ge; Zhangdaihong Liu; Xu Sun 001; Yang Yang 125; David A. Clifton (NeurIPS, 2022)

A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography. - Gert Mertes; Yuan Long; Zhangdaihong Liu; Yuhui Li; Yang Yang 125; David A. Clifton (Sensors, 2022)

A medical multimodal large language model for future pandemics. - Fenglin Liu; Tingting Zhu 001; Xian Wu 001; Bang Yang; Chenyu You; Chenyang Wang; Lei Lu; Zhangdaihong Liu; Yefeng Zheng 001; Xu Sun 001; Yang Yang 125; Lei A. Clifton; et al. (npj Digit. Medicine, 2023)

An adversarial training framework for mitigating algorithmic biases in clinical machine learning. - Jenny Yang; Andrew A. S. Soltan; David W. Eyre; Yang Yang 125; David A. Clifton (npj Digit. Medicine, 2023)

Privacy-Aware Early Detection of COVID-19 Through Adversarial Training. - Omid Rohanian; Samaneh Kouchaki; Andrew A. S. Soltan; Jenny Yang; Morteza Rohanian; Yang Yang 125; David A. Clifton (IEEE J. Biomed. Health Informatics, 2023)

Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention. - Zhangdaihong Liu; Ying Hu; Xuan Wu; Gert Mertes; Yang Yang 125; David A. Clifton (IEEE Trans. Biomed. Eng., 2023)

A Comparison of Representation Learning Methods for Medical Concepts in EHR Databases. - Zhangdaihong Liu; Xuan Wu; Yang Yang 125; David A. Clifton (BCB, 2024)

DuKA: A Dual-Keyless-Attention Model for Multi-Modality EHR Data Fusion and Organ Failure Prediction. - Zhangdaihong Liu; Xuan Wu; Yang Yang 125; David A. Clifton (IEEE Trans. Biomed. Eng., 2024)

Microtitre Plate Image Augmentation with Generative Adversarial Networks. - Ru Li 002; Tingting Chai; Samaneh Kouchaki; David A. Clifton; Yang Yang 125 (ICASSP, 2025)