Yikuan Li

Orcid: 0000-0001-7546-9979

According to our database1, Yikuan Li authored at least 30 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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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

Structural simulation and selective inhibitor discovery study for histone demethylases KDM4E/6B from a computational perspective.
Comput. Biol. Chem., 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

A comparative study of pretrained language models for long clinical text.
J. Am. Medical Informatics Assoc., January, 2023

Enhancing Health Data Interoperability with Large Language Models: A FHIR Study.
CoRR, 2023

Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources.
CoRR, 2023

Deep Reinforcement Learning for Cost-Effective Medical Diagnosis.
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

Multimodal machine learning in precision health: A scoping review.
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

Multimodal Machine Learning in Precision Health.
CoRR, 2022

Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences.
CoRR, 2022

2021
Disparities in Social Determinants among Performances of Mortality Prediction with Machine Learning for Sepsis Patients.
CoRR, 2021

Transfer Learning in Electronic Health Records through Clinical Concept Embedding.
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
BEHRT: Transformer for Electronic Health Records.
CoRR, 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


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