34 citations · 50 across the 6 of their papers we have counts for
6 papers
Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals
Xiao Gu, Wei Tang, Jinpei Han +10
Cardiac biosignals, such as electrocardiograms (ECG) and photoplethysmograms (PPG), are of paramount importance for the diagnosis, prevention, and management of cardiovascular dise…
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes
Vinod Kumar Chauhan, Lei Clifton, Gaurav Nigam +1
Estimating individualised treatment effect (ITE) -- that is the causal effect of a set of variables (also called exposures, treatments, actions, policies, or interventions), referr…
CE-SSL: Computation-Efficient Semi-Supervised Learning for ECG-based Cardiovascular Diseases Detection
Rushuang Zhou, Lei Clifton, Zijun Liu +4
The label scarcity problem is the main challenge that hinders the wide application of deep learning systems in automatic cardiovascular diseases (CVDs) detection using electrocardi…
Sample Selection Bias in Machine Learning for Healthcare
Vinod Kumar Chauhan, Lei Clifton, Achille Salaün +5
While machine learning algorithms hold promise for personalised medicine, their clinical adoption remains limited, partly due to biases that can compromise the reliability of predi…
Large Language Models in the Clinic: A Comprehensive Benchmark
Fenglin Liu, Zheng Li, Hongjian Zhou +16
The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention. Existing works mainly adopt the close-ended question-answering (QA) task with…
Lightweight Transformers for Clinical Natural Language Processing
Omid Rohanian, Mohammadmahdi Nouriborji, Hannah Jauncey +5
Specialised pre-trained language models are becoming more frequent in NLP since they can potentially outperform models trained on generic texts. BioBERT and BioClinicalBERT are two…