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2020 – today
- 2024
[j81]Vinod Kumar Chauhan, Jiandong Zhou, Ping Lu, Soheila Molaei, David A. Clifton:
A brief review of hypernetworks in deep learning. Artif. Intell. Rev. 57(9): 250 (2024)- [j80]Liangyi Lyu
, Lei Lu, Hanjie Chen, David A. Clifton, Yuanting Zhang, Tapabrata Chakraborti:
An improved deep regression model with state space reconstruction for continuous blood pressure estimation. Comput. Electr. Eng. 118: 109319 (2024) - [j79]Soheila Molaei, Nima Ghanbari Bousejin, Ghadeer O. Ghosheh, Anshul Thakur, Vinod Kumar Chauhan, Tingting Zhu, David A. Clifton:
CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks. J. Heal. Informatics Res. 8(3): 555-575 (2024) - [j78]Soheila Molaei, Ghazaleh Niknam, Ghadeer O. Ghosheh, Vinod Kumar Chauhan, Hadi Zare, Tingting Zhu, Shirui Pan, David A. Clifton:
Temporal dynamics unleashed: Elevating variational graph attention. Knowl. Based Syst. 299: 112110 (2024) - [j77]Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, Omid Rohanian, Soheila Molaei, David A. Clifton:
Continuous patient state attention model for addressing irregularity in electronic health records. BMC Medical Informatics Decis. Mak. 24(1): 117 (2024) - [j76]Jenny Yang, Hagen Triendl, Andrew A. S. Soltan, Mangal Prakash, David A. Clifton:
Addressing label noise for electronic health records: insights from computer vision for tabular data. BMC Medical Informatics Decis. Mak. 24(1): 183 (2024) - [j75]Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David W. Eyre, Lei Lu, David A. Clifton:
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. Mach. Learn. 113(5): 2655-2674 (2024) - [j74]Andrew P. Creagh, Valentin Hamy, Hang Yuan, Gert Mertes, Ryan Tomlinson, Wen-Hung Chen, Rachel Williams, Christopher Llop, Christopher Yee, Mei Sheng Duh, Aiden R. Doherty, Luis Garcia-Gancedo, David A. Clifton:
Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis. npj Digit. Medicine 7(1) (2024) - [j73]Hang Yuan, Shing Chan, Andrew P. Creagh, Catherine Tong, Aidan Acquah, David A. Clifton, Aiden R. Doherty:
Self-supervised learning for human activity recognition using 700,000 person-days of wearable data. npj Digit. Medicine 7(1) (2024) - [j72]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. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 3305-3320 (2024) - [j71]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. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5712-5724 (2024) - [j70]Zhangdaihong Liu, Xuan Wu, Yang Yang, David A. Clifton:
DuKA: A Dual-Keyless-Attention Model for Multi-Modality EHR Data Fusion and Organ Failure Prediction. IEEE Trans. Biomed. Eng. 71(4): 1247-1256 (2024) - [j69]Zhangdaihong Liu, Tingting Zhu, Lei Lu, Yuan-Ting Zhang, David A. Clifton:
Intelligent Electrocardiogram Acquisition Via Ubiquitous Photoplethysmography Monitoring. IEEE J. Biomed. Health Informatics 28(3): 1321-1330 (2024) - [j68]Anshul Thakur, Vinayak Abrol, Pulkit Sharma, Tingting Zhu, David A. Clifton:
Incremental Trainable Parameter Selection in Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6478-6491 (2024) - [c62]Soheila Molaei, Anshul Thakur, Ghazaleh Niknam, Andrew A. S. Soltan, Hadi Zare, David A. Clifton:
Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks. AISTATS 2024: 1342-1350 - [c61]Vinod Kumar Chauhan, Jiandong Zhou, Ghadeer O. Ghosheh, Soheila Molaei, David A. Clifton:
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation. AISTATS 2024: 3529-3537 - [c60]Shreyank N. Gowda, Boyan Gao, David A. Clifton:
FE-Adapter: Adapting Image-Based Emotion Classifiers to Videos. FG 2024: 1-6 - [i51]Omid Rohanian, Mohammadmahdi Nouriborji, David A. Clifton:
Exploring the Effectiveness of Instruction Tuning in Biomedical Language Processing. CoRR abs/2401.00579 (2024) - [i50]Niall Taylor, Upamanyu Ghose, Omid Rohanian, Mohammadmahdi Nouriborji, Andrey Kormilitzin, David A. Clifton, Alejo J. Nevado-Holgado:
Efficiency at Scale: Investigating the Performance of Diminutive Language Models in Clinical Tasks. CoRR abs/2402.10597 (2024) - [i49]James Anibal, Hannah Huth, Ming Li, Lindsey Hazen, Yen Minh Lam, Nguyen Thi Thu Hang, Michael Kleinman, Shelley Ost, Christopher Jackson, Laura Sprabery, Cheran Elangovan, Balaji Krishnaiah, Lee Akst, Ioan Lina, Iqbal Elyazar, Lenny Ekwati, Stefan Jansen, Richard Nduwayezu, Charisse Garcia, Jeffrey Plum, Jacqueline Brenner, Miranda Song, Emily Ricotta, David A. Clifton, Louise Thwaites, Yael Bensoussan, Bradford Wood:
Voice EHR: Introducing Multimodal Audio Data for Health. CoRR abs/2404.01620 (2024) - [i48]Andrew Liu, Hongjian Zhou, Yining Hua, Omid Rohanian, Lei A. Clifton, David A. Clifton:
Large Language Models in Healthcare: A Comprehensive Benchmark. CoRR abs/2405.00716 (2024) - [i47]Vinod Kumar Chauhan, Lei A. Clifton, Achille Salaün, Huiqi Yvonne Lu, Kim Branson, Patrick Schwab, Gaurav Nigam, David A. Clifton:
Sample Selection Bias in Machine Learning for Healthcare. CoRR abs/2405.07841 (2024) - [i46]Rushuang Zhou, Zijun Liu, Lei A. Clifton, David A. Clifton, Kannie W. Y. Chan, Yuan-Ting Zhang, Yining Dong:
Computation-Efficient Semi-Supervised Learning for ECG-based Cardiovascular Diseases Detection. CoRR abs/2406.14377 (2024) - [i45]Xingrun Xing, Boyan Gao, Zheng Zhang, David A. Clifton, Shitao Xiao, Li Du, Guoqi Li, Jiajun Zhang:
SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking. CoRR abs/2407.04752 (2024) - [i44]Omid Rohanian, Mohammadmahdi Nouriborji, Olena Seminog, Rodrigo Furst, Thomas Mendy, Shanthi Levanita, Zaharat Kadri-Alabi, Nusrat Jabin, Daniela Toale, Georgina S. Humphreys, Emilia Antonio, Adrian Bucher, Alice Norton, David A. Clifton:
Rapid Biomedical Research Classification: The Pandemic PACT Advanced Categorisation Engine. CoRR abs/2407.10086 (2024) - [i43]Shreyank N. Gowda, David A. Clifton:
Masks and Manuscripts: Advancing Medical Pre-training with End-to-End Masking and Narrative Structuring. CoRR abs/2407.16264 (2024) - [i42]Shreyank N. Gowda, David A. Clifton:
CC-SAM: SAM with Cross-feature Attention and Context for Ultrasound Image Segmentation. CoRR abs/2408.00181 (2024) - [i41]Shreyank N. Gowda, Boyan Gao, David A. Clifton:
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos. CoRR abs/2408.02421 (2024) - 2023
- [j67]Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki, David A. Clifton:
On the effectiveness of compact biomedical transformers. Bioinform. 39(3) (2023) - [j66]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) - [j65]Jenny Yang, Andrew A. S. Soltan, David W. Eyre, David A. Clifton:
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning. Nat. Mac. Intell. 5(8): 884-894 (2023) - [j64]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) - [j63]Fenglin Liu, Tingting Zhu, Xian Wu, Bang Yang, Chenyu You, Chenyang Wang, Lei Lu, Zhangdaihong Liu, Yefeng Zheng, Xu Sun, Yang Yang, Lei A. Clifton, David A. Clifton:
A medical multimodal large language model for future pandemics. npj Digit. Medicine 6 (2023) - [j62]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) - [j61]Peng Xu, Xiatian Zhu, David A. Clifton:
Multimodal Learning With Transformers: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 12113-12132 (2023) - [j60]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) - [j59]Ping Lu, Andrew P. Creagh, Huiqi Y. Lu, Ho Bich Hai, Louise Thwaites, David A. Clifton:
2D-WinSpatt-Net: A Dual Spatial Self-Attention Vision Transformer Boosts Classification of Tetanus Severity for Patients Wearing ECG Sensors in Low- and Middle-Income Countries. Sensors 23(18): 7705 (2023) - [j58]Huiqi Y. Lu, Ping Lu, Jane E. Hirst, Lucy Mackillop, David A. Clifton:
A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus. Sensors 23(18): 7990 (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) - [c59]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 - [c58]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 - [c57]Mohammadmahdi Nouriborji, Omid Rohanian, Samaneh Kouchaki, David A. Clifton:
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers. EACL 2023: 1153-1165 - [c56]Morteza Rohanian, Farhad Nooralahzadeh, Omid Rohanian, David A. Clifton, Michael Krauthammer:
Disfluent Cues for Enhanced Speech Understanding in Large Language Models. EMNLP (Findings) 2023: 3676-3684 - [c55]Ziyun Li, Xinshao Wang, Neil M. Robertson, David A. Clifton, Christoph Meinel, Haojin Yang:
SMKD: Selective Mutual Knowledge Distillation. IJCNN 2023: 1-8 - [c54]Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David A. Clifton, S. Kevin Zhou, Lawrence H. Staib, James S. Duncan:
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. NeurIPS 2023 - [c53]Marzia Hoque Tania, David A. Clifton:
Unleashing the Power of Federated Learning in Fragmented Digital Healthcare Systems: A Visionary Perspective. SKIMA 2023: 40-44 - [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 Y. 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]