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09/02/2023
RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model
Text-to-image generation (TTI) refers to the usage of models that could ...
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06/18/2023
Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction:A Multi-Dataset Study
Electrocardiography (ECG) is a non-invasive tool for predicting cardiova...
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06/12/2023
A Brief Review of Hypernetworks in Deep Learning
Hypernetworks, or hypernets in short, are neural networks that generate ...
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05/25/2023
Dynamic Inter-treatment Information Sharing for Heterogeneous Treatment Effects Estimation
Existing heterogeneous treatment effects learners, also known as conditi...
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05/05/2023
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
The lack of data democratization and information leakage from trained mo...
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03/11/2023
ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation
Natural Language Generation (NLG) accepts input data in the form of imag...
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02/28/2023
Synthesizing Mixed-type Electronic Health Records using Diffusion Models
Electronic Health Records (EHRs) contain sensitive patient information, ...
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02/09/2023
Lightweight Transformers for Clinical Natural Language Processing
Specialised pre-trained language models are becoming more frequent in NL...
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02/03/2023
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
For medical image segmentation, contrastive learning is the dominant pra...
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11/21/2022
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
Most video-and-language representation learning approaches employ contra...
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10/23/2022
Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions
The "Patient Instruction" (PI), which contains critical instructional in...
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10/12/2022
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers
Pre-trained Language Models (LMs) have become an integral part of Natura...
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09/07/2022
On the Effectiveness of Compact Biomedical Transformers
Language models pre-trained on biomedical corpora, such as BioBERT, have...
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08/05/2022
COPER: Continuous Patient State Perceiver
In electronic health records (EHRs), irregular time-series (ITS) occur n...
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07/24/2022
Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling
A particular challenge for disease progression modeling is the heterogen...
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06/30/2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State
To train robust deep neural networks (DNNs), we systematically study sev...
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06/13/2022
Multimodal Learning with Transformers: A Survey
Transformer is a promising neural network learner, and has achieved grea...
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06/06/2022
Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data
Advances in deep learning for human activity recognition have been relat...
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05/24/2022
Deep Reinforcement Learning for Multi-class Imbalanced Training
With the rapid growth of memory and computing power, datasets are becomi...
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02/08/2022
How to Understand Masked Autoencoders
"Masked Autoencoders (MAE) Are Scalable Vision Learners" revolutionizes ...
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07/04/2021
Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
Given the abundance and ease of access of personal data today, individua...
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06/02/2021
Not All Knowledge Is Created Equal
Mutual knowledge distillation (MKD) improves a model by distilling knowl...
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11/28/2020
DROPS: Deep Retrieval of Physiological Signals via Attribute-specific Clinical Prototypes
The ongoing digitization of health records within the healthcare industr...
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11/28/2020
PCPs: Patient Cardiac Prototypes
Many clinical deep learning algorithms are population-based and difficul...
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05/27/2020
CLOCS: Contrastive Learning of Cardiac Signals
The healthcare industry generates troves of unlabelled physiological dat...
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04/22/2020
SoQal: Selective Oracle Questioning in Active Learning
Large sets of unlabelled data within the healthcare domain remain underu...
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04/20/2020
CLOPS: Continual Learning of Physiological Signals
Deep learning algorithms are known to experience destructive interferenc...
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04/20/2020
ALPS: Active Learning via Perturbations
Small, labelled datasets in the presence of larger, unlabelled datasets ...
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12/10/2019
Severity Detection Tool for Patients with Infectious Disease
Hand, foot and mouth disease (HFMD) and tetanus are serious infectious d...
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12/01/2019
