Yikuan Li
Orcid: 0000-0001-7546-9979
According to our database1,
Yikuan Li
authored at least 29 papers
between 2018 and 2024.
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Bibliography
2024
Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records.
IEEE Trans. Neural Networks Learn. Syst., April, 2024
2023
AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease.
J. Biomed. Informatics, August, 2023
Patterns of diverse and changing sentiments towards COVID-19 vaccines: a sentiment analysis study integrating 11 million tweets and surveillance data across over 180 countries.
J. Am. Medical Informatics Assoc., April, 2023
Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records.
IEEE J. Biomed. Health Informatics, February, 2023
J. Am. Medical Informatics Assoc., January, 2023
CoRR, 2023
Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources.
CoRR, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure.
IEEE J. Biomed. Health Informatics, 2022
npj Digit. Medicine, 2022
Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants.
BMC Medical Informatics Decis. Mak., 2022
AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease.
CoRR, 2022
Deep Learning Reveals Patterns of Diverse and Changing Sentiments Towards COVID-19 Vaccines Based on 11 Million Tweets.
CoRR, 2022
Clinical outcome prediction under hypothetical interventions - a representation learning framework for counterfactual reasoning.
CoRR, 2022
CoRR, 2022
2021
Disparities in Social Determinants among Performances of Mortality Prediction with Machine Learning for Sepsis Patients.
CoRR, 2021
CoRR, 2021
Risk factor identification for incident heart failure using neural network distillation and variable selection.
CoRR, 2021
An explainable Transformer-based deep learning model for the prediction of incident heart failure.
CoRR, 2021
Early Prediction of Mortality in Critical Care Setting in Sepsis Patients Using Structured Features and Unstructured Clinical Notes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
Learning multimorbidity patterns from electronic health records using Non-negative Matrix Factorisation.
J. Biomed. Informatics, 2020
Deep Bayesian Gaussian Processes for Uncertainty Estimation in Electronic Health Records.
CoRR, 2020
Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network.
Artif. Intell. Medicine, 2020
A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
Learning Multimorbidity Patterns from Electronic Health Records Using Non-negative Matrix Factorisation.
CoRR, 2019
Using Machine Learning to Integrate Socio-Behavioral Factors in Predicting Cardiovascular-Related Mortality Risk.
Proceedings of the MEDINFO 2019: Health and Wellbeing e-Networks for All, 2019
2018
Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018