Area of research
Artificial Intelligence · Biomedical Engineering
Research interest
Research interests include Machine Learning in Healthcare, Non-Invasive Vital Sign Monitoring, Healthcare Technology and Patient Monitoring, and Topic Modeling.
Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling Under Data-View Heterogeneity
Mitigating algorithmic unfairness arising from forgetfulness of medical records in clinical artificial intelligence.
Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals.
Drug or Pokémon? Large language model performance in identification of fabricated medications
Application of large language models in medicine
Application of large language models in medicine
RenAIssance: A Survey Into AI Text-to-Image Generation in the Era of Large Model
A scoping review of large language models for generative tasks in mental health care.
Sample Selection Bias in Machine Learning for Healthcare
Denoising Reuse: Exploiting Inter-Frame Motion Consistency for Efficient Video Generation
Aligning, Autoencoding and Prompting Large Language Models for Novel Disease Reporting.
A multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis.
Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model.
MISE: Meta-knowledge Inheritance for Social Media-Based Stressor Estimation
AI-Assisted in Silico Trial for the Optimization of Osmotherapy After Ischaemic Stroke
Correction: Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation.
Correction: Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation (Preprint)
Characterising Parkinson's Disease-like Walking Using Wrist-worn Accelerometers
Efficient Task Grouping Through Sample-Wise Optimisation Landscape Analysis
Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes
Generalizability assessment of AI models across hospitals in a low-middle and high income country.
RenAIssance: A Survey Into AI Text-to-Image Generation in the Era of Large Model
Mine Your Own Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels.
Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification
Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction: A Multi-Dataset Study.
Predicting future hospital antimicrobial resistance prevalence using machine learning.
Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review.
DuKA: A Dual-Keyless-Attention Model for Multi-Modality EHR Data Fusion and Organ Failure Prediction
Predicting individual patient and hospital-level discharge using machine learning.
ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation.