IoT health devices: exploring security risks in the connected landscape
The concept of the Internet of Things (IoT) spans decades, and the same can be said for its
inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable …
inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable …
Deep learning for personalized electrocardiogram diagnosis: A review
The electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its
interpretation traditionally reliant on the expertise of cardiologists. The emergence of deep …
interpretation traditionally reliant on the expertise of cardiologists. The emergence of deep …
Exploration of quantum neural architecture by mixing quantum neuron designs
With the constant increase of the number of quantum bits (qubits) in the actual quantum
computers, implementing and accelerating the prevalent deep learning on quantum …
computers, implementing and accelerating the prevalent deep learning on quantum …
FedCross: Towards accurate federated learning via multi-model cross-aggregation
As a promising distributed machine learning paradigm, Federated Learning (FL) has
attracted increasing attention to deal with data silo problems without compromising user …
attracted increasing attention to deal with data silo problems without compromising user …
Lightweight run-time working memory compression for deployment of deep neural networks on resource-constrained MCUs
This work aims to achieve intelligence on embedded devices by deploying deep neural
networks (DNNs) onto resource-constrained microcontroller units (MCUs). Apart from the …
networks (DNNs) onto resource-constrained microcontroller units (MCUs). Apart from the …
Diachronic and synchronic variation in the performance of adaptive machine learning systems: the ethical challenges
J Hatherley, R Sparrow - Journal of the American Medical …, 2023 - academic.oup.com
Objectives Machine learning (ML) has the potential to facilitate “continual learning” in
medicine, in which an ML system continues to evolve in response to exposure to new data …
medicine, in which an ML system continues to evolve in response to exposure to new data …
Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation
The MRI-derived brain network serves as a pivotal instrument in elucidating both the
structural and functional aspects of the brain, encompassing the ramifications of diseases …
structural and functional aspects of the brain, encompassing the ramifications of diseases …
MetaVA: Curriculum meta-learning and pre-fine-tuning of deep neural networks for detecting ventricular arrhythmias based on ECGs
W Zhang, S Geng, Z Fu, L Zheng, C Jiang… - arXiv preprint arXiv …, 2022 - arxiv.org
Ventricular arrhythmias (VA) are the main causes of sudden cardiac death. Developing
machine learning methods for detecting VA based on electrocardiograms (ECGs) can help …
machine learning methods for detecting VA based on electrocardiograms (ECGs) can help …
Short: VANet: An Intuitive Light-Weight Deep Learning Solution Towards Ventricular Arrhythmia Detection
Ventricular Arrhythmia (VA) is a leading cause of sudden cardiac death (SCD), which kills an
average of 180,000 to 350,000 people annually, accounting for 15%–20% of all deaths …
average of 180,000 to 350,000 people annually, accounting for 15%–20% of all deaths …
On-device prior knowledge incorporated learning for personalized atrial fibrillation detection
Atrial Fibrillation (AF), one of the most prevalent arrhythmias, is an irregular heart-rate
rhythm causing serious health problems such as stroke and heart failure. Deep learning …
rhythm causing serious health problems such as stroke and heart failure. Deep learning …