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2020 – today
- 2023
[j62]Ghazaleh Niknam, Soheila Molaei, Hadi Zare, David A. Clifton, Shirui Pan:
Graph representation learning based on deep generative gaussian mixture models. Neurocomputing 523: 157-169 (2023)- [j61]Ghazaleh Niknam
, Soheila Molaei, Hadi Zare, Shirui Pan, Mahdi Jalili, Tingting Zhu, David A. Clifton:
DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks. Neural Networks 165: 596-610 (2023) - [j60]Jenny Yang, Andrew A. S. Soltan, David W. Eyre, Yang Yang, David A. Clifton:
An adversarial training framework for mitigating algorithmic biases in clinical machine learning. npj Digit. Medicine 6 (2023) - [j59]Peng Xu, Xiatian Zhu, David A. Clifton:
Multimodal Learning With Transformers: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 12113-12132 (2023) - [j58]Atieh Khodadadi, Nima Ghanbari Bousejin, Soheila Molaei, Vinod Kumar Chauhan, Tingting Zhu, David A. Clifton:
Improving Diagnostics with Deep Forest Applied to Electronic Health Records. Sensors 23(14): 6571 (2023) - [j57]Ping Lu, Chenyang Wang, Jannis Hagenah, Shadi Ghiasi, VITAL Consortium, Tingting Zhu, Louise Thwaites, David A. Clifton:
Improving Classification of Tetanus Severity for Patients in Low-Middle Income Countries Wearing ECG Sensors by Using a CNN-Transformer Network. IEEE Trans. Biomed. Eng. 70(4): 1340-1350 (2023) - [j56]Zhangdaihong Liu, Ying Hu, Xuan Wu, Gert Mertes, Yang Yang, David A. Clifton:
Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention. IEEE Trans. Biomed. Eng. 70(8): 2329-2337 (2023) - [j55]Lei Lu, Ying Tan, Denny Oetomo, Iven Mareels, David A. Clifton:
Weak Monotonicity With Trend Analysis for Unsupervised Feature Evaluation. IEEE Trans. Cybern. 53(11): 6883-6895 (2023) - [j54]Omid Rohanian, Samaneh Kouchaki, Andrew A. S. Soltan, Jenny Yang, Morteza Rohanian, Yang Yang, David A. Clifton:
Privacy-Aware Early Detection of COVID-19 Through Adversarial Training. IEEE J. Biomed. Health Informatics 27(3): 1249-1258 (2023) - [j53]Anshul Thakur, Jacob Armstrong, Alexey Youssef, David W. Eyre, David A. Clifton:
Self-Aware SGD: Reliable Incremental Adaptation Framework for Clinical AI Models. IEEE J. Biomed. Health Informatics 27(3): 1624-1634 (2023) - [j52]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
PCPs: Patient Cardiac Prototypes to Probe AI-based Medical Diagnoses, Distill Datasets, and Retrieve Patients. Trans. Mach. Learn. Res. 2023 (2023) - [c56]Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu, David A. Clifton:
Adversarial De-confounding in Individualised Treatment Effects Estimation. AISTATS 2023: 837-849 - [c55]Omid Rohanian, Hannah Jauncey, Mohammadmahdi Nouriborji, Vinod Kumar, Bronner P. Gonçalves, Christiana Kartsonaki, Isaric Clinical Characterisation Group, Laura Merson, David A. Clifton:
Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints. BioNLP@ACL 2023: 62-78 - [c54]Mohammadmahdi Nouriborji, Omid Rohanian, Samaneh Kouchaki, David A. Clifton:
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers. EACL 2023: 1153-1165 - [c53]Ziyun Li, Xinshao Wang, Neil M. Robertson, David A. Clifton, Christoph Meinel, Haojin Yang:
SMKD: Selective Mutual Knowledge Distillation. IJCNN 2023: 1-8 - [i40]Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, Xiaoran Zhang, Chen Feng, David A. Clifton, S. Kevin Zhou, Lawrence Hamilton Staib, James S. Duncan:
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. CoRR abs/2302.01735 (2023) - [i39]Omid Rohanian, Mohammadmahdi Nouriborji, Hannah Jauncey, Samaneh Kouchaki, Lei A. Clifton, Laura Merson, David A. Clifton:
Lightweight Transformers for Clinical Natural Language Processing. CoRR abs/2302.04725 (2023) - [i38]Taha Ceritli, Ghadeer O. Ghosheh, Vinod Kumar Chauhan, Tingting Zhu, Andrew P. Creagh, David A. Clifton:
Synthesizing Mixed-type Electronic Health Records using Diffusion Models. CoRR abs/2302.14679 (2023) - [i37]Bang Yang, Fenglin Liu, Yuexian Zou, Xian Wu, Yaowei Wang, David A. Clifton:
ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation. CoRR abs/2303.06458 (2023) - [i36]Alexey Youssef, Michael Pencina, Anshul Thakur, Tingting Zhu, David A. Clifton, Nigam H. Shah:
All models are local: time to replace external validation with recurrent local validation. CoRR abs/2305.03219 (2023) - [i35]Anshul Thakur, Tingting Zhu, Vinayak Abrol, Jacob Armstrong, Yujiang Wang, David A. Clifton:
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention. CoRR abs/2305.03710 (2023) - [i34]Yujiang Wang, Anshul Thakur, Mingzhi Dong, Pingchuan Ma, Stavros Petridis, Li Shang, Tingting Zhu, David A. Clifton:
Is dataset condensation a silver bullet for healthcare data sharing? CoRR abs/2305.03711 (2023) - [i33]Vinod Kumar Chauhan, Jiandong Zhou, Soheila Molaei, Ghadeer O. Ghosheh, David A. Clifton:
Dynamic Inter-treatment Information Sharing for Heterogeneous Treatment Effects Estimation. CoRR abs/2305.15984 (2023) - [i32]Vinod Kumar Chauhan, Jiandong Zhou, Ping Lu, Soheila Molaei, David A. Clifton:
A Brief Review of Hypernetworks in Deep Learning. CoRR abs/2306.06955 (2023) - [i31]Rushuang Zhou, Lei Lu, Zijun Liu, Ting Xiang, Zhen Liang, David A. Clifton, Yining Dong, Yuan-Ting Zhang:
Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction: A Multi-Dataset Study. CoRR abs/2306.10494 (2023) - [i30]Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song:
RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model. CoRR abs/2309.00810 (2023) - 2022
- [j51]Jenny Yang, Andrew A. S. Soltan, David A. Clifton:
Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening. npj Digit. Medicine 5 (2022) - [j50]Gert Mertes, Yuan Long, Zhangdaihong Liu, Yuhui Li, Yang Yang, David A. Clifton:
A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography. Sensors 22(9): 3303 (2022) - [j49]Shadi Ghiasi, Tingting Zhu, Ping Lu, Jannis Hagenah, Phan Nguyen Quoc Khanh, Nguyen Van Hao, VITAL Consortium, Louise Thwaites, David A. Clifton:
Sepsis Mortality Prediction Using Wearable Monitoring in Low-Middle Income Countries. Sensors 22(10): 3866 (2022) - [j48]Jenny Yang, David A. Clifton, Jane E. Hirst, Foteini K. Kavvoura, George Farah, Lucy Mackillop, Huiqi Lu:
Machine Learning-Based Risk Stratification for Gestational Diabetes Management. Sensors 22(13): 4805 (2022) - [j47]Ping Lu, Shadi Ghiasi, Jannis Hagenah, Ho Bich Hai, Nguyen Van Hao, Phan Nguyen Quoc Khanh, Le Dinh Van Khoa, VITAL Consortium, Louise Thwaites, David A. Clifton, Tingting Zhu:
Classification of Tetanus Severity in Intensive-Care Settings for Low-Income Countries Using Wearable Sensing. Sensors 22(17): 6554 (2022) - [j46]Pulkit Sharma, Farah E. Shamout, Vinayak Abrol, David A. Clifton:
Data Pre-Processing Using Neural Processes for Modeling Personalized Vital-Sign Time-Series Data. IEEE J. Biomed. Health Informatics 26(4): 1528-1537 (2022) - [j45]Anshul Thakur, Pulkit Sharma, David A. Clifton:
Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications. IEEE J. Biomed. Health Informatics 26(4): 1761-1772 (2022) - [c52]Jacob Armstrong, David A. Clifton:
Continual learning of longitudinal health records. BHI 2022: 1-6 - [c51]Taha Ceritli, Andrew P. Creagh, David A. Clifton:
Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling. BHI 2022: 1-8 - [c50]Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, David A. Clifton:
COPER: Continuous Patient State Perceiver. BHI 2022: 1-4 - [c49]Lei Lu, Tingting Zhu, Yuan-Ting Zhang, David A. Clifton:
Spectrum Estimation of Heart Rate Variability Using Low-rank Matrix Completion. BHI 2022: 1-4 - [c48]Taha Ceritli, Andrew P. Creagh, David A. Clifton:
Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling. Healthcare AI and COVID-19 Workshop 2022: 41-53 - [c47]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals. ICML 2022: 11302-11340 - [c46]Peng Jin, Jinfa Huang, Fenglin Liu, Xian Wu, Shen Ge, Guoli Song, David A. Clifton, Jie Chen:
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations. NeurIPS 2022 - [c45]Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu Sun, Yang Yang, David A. Clifton:
Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions. NeurIPS 2022 - [c44]Mohammadmahdi Nouriborji, Omid Rohanian, David A. Clifton:
Nowruz at SemEval-2022 Task 7: Tackling Cloze Tests with Transformers and Ordinal Regression. SemEval@NAACL 2022: 1071-1077 - [e1]Peng Xu, Tingting Zhu, Pengkai Zhu, David A. Clifton, Danielle Belgrave, Yuanting Zhang:
Proceedings of the 1st Workshop on Healthcare AI and COVID-19, 22 July 2022, Baltimore, Maryland, USA. Proceedings of Machine Learning Research 184, PMLR 2022 [contents] - [d1]Heloise Greeff, A. Manandhar, Patrick Thomson, Robert Hope, David A. Clifton:
Condition Monitoring for Handpumps - vibration data. IEEE DataPort, 2022
- [i29]Omid Rohanian, Samaneh Kouchaki, Andrew A. S. Soltan, Jenny Yang, Morteza Rohanian, Yang Yang, David A. Clifton:
Privacy-aware Early Detection of COVID-19 through Adversarial Training. CoRR abs/2201.03004 (2022) - [i28]Shuhao Cao, Peng Xu, David A. Clifton:
How to Understand Masked Autoencoders. CoRR abs/2202.03670 (2022) - [i27]Mohammadmahdi Nouriborji, Omid Rohanian, David A. Clifton:
Nowruz at SemEval-2022 Task 7: Tackling Cloze Tests with Transformers and Ordinal Regression. CoRR abs/2204.00556 (2022) - [i26]Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David A. Clifton:
Deep Reinforcement Learning for Multi-class Imbalanced Training. CoRR abs/2205.12070 (2022) - [i25]Hang Yuan, Shing Chan, Andrew P. Creagh, Catherine Tong, David A. Clifton, Aiden R. Doherty:
Self-supervised Learning for Human Activity Recognition Using 700, 000 Person-days of Wearable Data. CoRR abs/2206.02909 (2022) - [i24]Peng Xu, Xiatian Zhu, David A. Clifton:
Multimodal Learning with Transformers: A Survey. CoRR abs/2206.06488 (2022) - [i23]Xinshao Wang, Yang Hua, Elyor Kodirov, Sankha Subhra Mukherjee, David A. Clifton, Neil M. Robertson:
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State. CoRR abs/2207.00118 (2022) - [i22]Taha Ceritli, Andrew P. Creagh, David A. Clifton:
Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling. CoRR abs/2207.11846 (2022) - [i21]Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, David A. Clifton:
COPER: Continuous Patient State Perceiver. CoRR abs/2208.03196 (2022) - [i20]Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki, David A. Clifton:
On the Effectiveness of Compact Biomedical Transformers. CoRR abs/2209.03182 (2022) - [i19]Mohammadmahdi Nouriborji, Omid Rohanian, Samaneh Kouchaki, David A. Clifton:
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers. CoRR abs/2210.06425 (2022) - [i18]Omid Rohanian, Hannah Jauncey, Mohammadmahdi Nouriborji, Bronner P. Gonçalves, Christiana Kartsonaki, Laura Merson, David A. Clifton:
Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints. CoRR abs/2210.09440 (2022) - [i17]Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu, David A. Clifton:
Adversarial De-confounding in Individualised Treatment Effects Estimation. CoRR abs/2210.10530 (2022) - [i16]Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu Sun, Yang Yang, David A. Clifton:
Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions. CoRR abs/2210.12777 (2022) - [i15]Peng Jin, Jinfa Huang, Fenglin Liu, Xian Wu, Shen Ge, Guoli Song, David A. Clifton, Jie Chen:
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations. CoRR abs/2211.11427 (2022) - 2021
- [j44]Yang Yang, Timothy M. Walker, Samaneh Kouchaki, Chenyang Wang, Timothy E. A Peto, Derrick W. Crook, David A. Clifton:
An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction. Briefings Bioinform. 22(6) (2021) - [j43]Peter H. Charlton, Timothy Bonnici, Lionel Tarassenko, David A. Clifton, Richard Beale, Peter J. Watkinson, Jordi Alastruey:
An impedance pneumography signal quality index: Design, assessment and application to respiratory rate monitoring. Biomed. Signal Process. Control. 65: 102339 (2021) - [j42]Matthew Chun, Robert Clarke, Benjamin J. Cairns, David A. Clifton, Derrick Bennett, Yiping Chen, Yu Guo, Pei Pei, Jun Lv, Canqing Yu, Ling Yang, Liming Li, Zhengming Chen, Tingting Zhu:
Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults. J. Am. Medical Informatics Assoc. 28(8): 1719-1727 (2021) - [j41]Davide Morelli, Alessio Rossi, Leonardo Bartoloni, Massimo Cairo, David A. Clifton:
SDNN24 Estimation from Semi-Continuous HR Measures. Sensors 21(4): 1463 (2021) - [j40]Xinyu Jiang, Ke Xu, Xiangyu Liu, Chenyun Dai, David A. Clifton, Edward A. Clancy, Metin Akay, Wei Chen:
Neuromuscular Password-Based User Authentication. IEEE Trans. Ind. Informatics 17(4): 2641-2652 (2021) - [j39]Rasheed el-Bouri, David W. Eyre, Peter J. Watkinson, Tingting Zhu, David A. Clifton:
Hospital Admission Location Prediction via Deep Interpretable Networks for the Year-Round Improvement of Emergency Patient Care. IEEE J. Biomed. Health Informatics 25(1): 289-300 (2021) - [j38]Nan Ji, Ting Xiang, Paolo Bonato, Nigel H. Lovell, Sze-Yuan Ooi, David A. Clifton, Metin Akay, Xiao-Rong Ding, Bryan P. Yan, Vincent C. T. Mok, Dimitrios I. Fotiadis, Yuan-Ting Zhang:
Recommendation to Use Wearable-Based mHealth in Closed-Loop Management of Acute Cardiovascular Disease Patients During the COVID-19 Pandemic. IEEE J. Biomed. Health Informatics 25(4): 903-908 (2021) - [j37]Xinyu Jiang, Ke Xu, Xiangyu Liu, Chenyun Dai, David A. Clifton, Edward A. Clancy, Metin Akay, Wei Chen:
Cancelable HD-sEMG-Based Biometrics for Cross-Application Discrepant Personal Identification. IEEE J. Biomed. Health Informatics 25(4): 1070-1079 (2021) - [j36]Ting Xiang, Nan Ji, David A. Clifton, Lei Lu, Yuan-Ting Zhang:
Interactive Effects of HRV and P-QRS-T on the Power Density Spectra of ECG Signals. IEEE J. Biomed. Health Informatics 25(11): 4163-4174 (2021) - [c43]Xinshao Wang, Yang Hua, Elyor Kodirov, David A. Clifton, Neil M. Robertson:
ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks. CVPR 2021: 752-761 - [c42]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients. ICML 2021: 5606-5615 - [c41]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age. NeurIPS 2021: 15557-15569 - [i14]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
Let Your Heart Speak in its Mother Tongue: Multilingual Captioning of Cardiac Signals. CoRR abs/2103.11011 (2021) - [i13]Ziyun Li, Xinshao Wang, Haojin Yang, Di Hu, Neil Martin Robertson, David A. Clifton, Christoph Meinel:
Not All Knowledge Is Created Equal. CoRR abs/2106.01489 (2021) - [i12]Rasheed el-Bouri, Tingting Zhu, David A. Clifton:
Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning. CoRR abs/2107.01707 (2021) - [i11]Jacob Armstrong, David A. Clifton:
Continual learning of longitudinal health records. CoRR abs/2112.11944 (2021) - 2020
- [j35]Alessio Rossi, Eleonora Da Pozzo, Dario Menicagli, Chiara Tremolanti, Corrado Priami, Alina Sîrbu, David A. Clifton, Claudia Martini, Davide Morelli:
A Public Dataset of 24-h Multi-Levels Psycho-Physiological Responses in Young Healthy Adults. Data 5(4): 91 (2020) - [j34]Alessio Rossi, Dino Pedreschi, David A. Clifton, Davide Morelli:
Error Estimation of Ultra-Short Heart Rate Variability Parameters: Effect of Missing Data Caused by Motion Artifacts. Sensors 20(24): 7122 (2020) - [j33]Farah E. Shamout, Tingting Zhu, Pulkit Sharma, Peter J. Watkinson, David A. Clifton:
Deep Interpretable Early Warning System for the Detection of Clinical Deterioration. IEEE J. Biomed. Health Informatics 24(2): 437-446 (2020) - [j32]Wei Chen, David A. Clifton, Brian A. Telfer:
Guest Editorial: Integrative Sensor Networks, Informatics, and Modeling for Precision and Preventative Medicine. IEEE J. Biomed. Health Informatics 24(7): 1858-1859 (2020) - [j31]Girmaw Abebe Tadesse, Hamza A. Javed, Nhan Le Nguyen Thanh, Ha Thi Hai Duong, Le Van Tan, Louise Thwaites, David A. Clifton, Tingting Zhu:
Multi-Modal Diagnosis of Infectious Diseases in the Developing World. IEEE J. Biomed. Health Informatics 24(7): 2131-2141 (2020) - [j30]Dani Kiyasseh, Girmaw Abebe Tadesse, Nhan Le Nguyen Thanh, Le Van Tan, Louise Thwaites, Tingting Zhu, David A. Clifton:
PlethAugment: GAN-Based PPG Augmentation for Medical Diagnosis in Low-Resource Settings. IEEE J. Biomed. Health Informatics 24(11): 3226-3235 (2020) - [c40]Rasheed el-Bouri, David W. Eyre, Peter J. Watkinson, Tingting Zhu, David A. Clifton:
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location. ICML 2020: 2848-2857 - [i10]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
ALPS: Active Learning via Perturbations. CoRR abs/2004.09557 (2020) - [i9]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
CLOPS: Continual Learning of Physiological Signals. CoRR abs/2004.09578 (2020) - [i8]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
SoQal: Selective Oracle Questioning in Active Learning. CoRR abs/2004.10468 (2020) - [i7]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
CLOCS: Contrastive Learning of Cardiac Signals. CoRR abs/2005.13249 (2020) - [i6]Rasheed el-Bouri, David W. Eyre, Peter J. Watkinson, Tingting Zhu, David A. Clifton:
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location. CoRR abs/2007.01135 (2020) - [i5]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
PCPs: Patient Cardiac Prototypes. CoRR abs/2011.14227 (2020) - [i4]Dani Kiyasseh, Tingting Zhu, David A. Clifton:
DROPS: Deep Retrieval of Physiological Signals via Attribute-specific Clinical Prototypes. CoRR abs/2011.14230 (2020)
2010 – 2019
- 2019
- [j29]Tingting Zhu, Glen Wright Colopy, Glenn H. MacEwen, Katherine E. Niehaus, Yang Yang, Chris W. Pugh, David A. Clifton:
Patient-Specific Physiological Monitoring and Prediction Using Structured Gaussian Processes. IEEE Access 7: 58094-58103 (2019) - [j28]Samaneh Kouchaki, Yang Yang, Timothy M. Walker, A. Sarah Walker, Daniel J. Wilson, Timothy E. A Peto, Derrick W. Crook, CRyPTIC Consortium, David A. Clifton:
Application of machine learning techniques to tuberculosis drug resistance analysis. Bioinform. 35(13): 2276-2282 (2019) - [j27]Yang Yang, Timothy M. Walker, A. Sarah Walker, Daniel J. Wilson, Timothy E. A Peto, Derrick W. Crook, Farah Shamout, CRyPTIC Consortium, Tingting Zhu, David A. Clifton:
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis. Bioinform. 35(18): 3240-3249 (2019) - [j26]James Malycha, Timothy Bonnici, David A. Clifton, Guy Ludbrook, J. Duncan Young, Peter J. Watkinson:
Patient centred variables with univariate associations with unplanned ICU admission: a systematic review. BMC Medical Informatics Decis. Mak. 19(1): 98:1-98:9 (2019) - [j25]Davide Morelli, Alessio Rossi, Massimo Cairo, David A. Clifton:
Analysis of the Impact of Interpolation Methods of Missing RR-intervals Caused by Motion Artifacts on HRV Features Estimations. Sensors 19(14): 3163 (2019) - [j24]Tingting Zhu, Marco A. F. Pimentel, Gari D. Clifford, David A. Clifton:
Unsupervised Bayesian Inference to Fuse Biosignal Sensory Estimates for Personalizing Care. IEEE J. Biomed. Health Informatics 23(1): 47-58 (2019) - [j23]Glen Wright Colopy, Stephen J. Roberts, David A. Clifton:
Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward. IEEE J. Biomed. Health Informatics 23(3): 949-959 (2019) - [c39]Girmaw Abebe Tadesse, Tingting Zhu, Yong Liu, Yingling Zhou, Jiyan Chen, Maoyi Tian, David A. Clifton:
Cardiovascular disease diagnosis using cross-domain transfer learning. EMBC 2019: 4262-4265 - [i3]Pulkit Sharma, Farah E. Shamout, David A. Clifton:
Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality. CoRR abs/1912.00354 (2019) - [i2]Girmaw Abebe Tadesse, Tingting Zhu, Nhan Le Nguyen Thanh, Nguyen Thanh Hung, Ha Thi Hai Duong, Truong Huu Khanh, Pham Van Quang, Duc Duong Tran, LamMinh Yen, H. Rogier Van Doorn, Nguyen Van Hao, John Prince, Hamza A. Javed, Dani Kiyasseh, Le Van Tan, Louise Thwaites, David A. Clifton:
Severity Detection Tool for Patients with Infectious Disease. CoRR abs/1912.05345 (2019) - 2018
- [j22]Yang Yang, Katherine E. Niehaus, Timothy M. Walker, Zamin Iqbal, A. Sarah Walker, Daniel J. Wilson, Tim E. A. Peto, Derrick W. Crook, E. Grace Smith, Tingting Zhu, David A. Clifton:
Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data. Bioinform. 34(10): 1666-1671 (2018) - [j21]Stijn Luca, Marco A. F. Pimentel, Peter J. Watkinson, David A. Clifton:
Point process models for novelty detection on spatial point patterns and their extremes. Comput. Stat. Data Anal. 125: 86-103 (2018) - [j20]Delaram Jarchi, Dario Salvi, Lionel Tarassenko, David A. Clifton:
Validation of Instantaneous Respiratory Rate Using Reflectance PPG from Different Body Positions. Sensors 18(11): 3705 (2018) - [j19]Drew A. Birrenkott, Marco A. F. Pimentel, Peter J. Watkinson, David A. Clifton:
A Robust Fusion Model for Estimating Respiratory Rate From Photoplethysmography and Electrocardiography. IEEE Trans. Biomed. Eng. 65(9): 2033-2041 (2018) - [j18]Glen Wright Colopy, Stephen J. Roberts, David A. Clifton:
Bayesian Optimization of Personalized Models for Patient Vital-Sign Monitoring. IEEE J. Biomed. Health Informatics 22(2): 301-310 (2018) - [c38]Tingting Zhu, Glen Wright Colopy, Chris W. Pugh, David A. Clifton:
Identifying patient-specific trajectories in haemodialysis using Bayesian Hierarchical Gaussian Processes. BHI 2018: 186-189 - [c37]Delaram Jarchi, Dario Salvi, Carmelo Velardo, Adam Mahdi, Lionel Tarassenko, David A. Clifton:
Estimation of HRV and SpO2 from wrist-worn commercial sensors for clinical settings. BSN 2018: 144-147 - [c36]Delaram Jarchi, Adam Mahdi, Lionel Tarassenko, David A. Clifton:
Visualisation of long-term ECG signals applied to post-intensive care patients. BSN 2018: 165-168 - 2017
- [j17]