AI Medical Compendium Topic

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Signal Processing, Computer-Assisted

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Supervised Contrastive Learning-Based Domain Generalization Network for Cross-Subject Motor Decoding.

IEEE transactions on bio-medical engineering
Developing an electroencephalogram (EEG)-based motor imagery and motor execution (MI/ME) decoding system that is both highly accurate and calibration-free for cross-subject applications remains challenging due to domain shift problem inherent in such...

Interpretable machine learning models for COPD ease of breathing estimation.

Medical & biological engineering & computing
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide and greatly reduces the quality of life. Utilizing remote monitoring has been shown to improve quality of life and reduce exacerbations, but remains an ongoing area of...

A multi-level feature fusion artificial neural network for classification of acoustic emission signals.

Annals of the New York Academy of Sciences
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract ...

Spiking-PhysFormer: Camera-based remote photoplethysmography with parallel spike-driven transformer.

Neural networks : the official journal of the International Neural Network Society
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, ...

Deep Power-Aware Tunable Weighting for Ultrasound Microvascular Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound microvascular imaging (UMI), including ultrafast power Doppler imaging (uPDI) and ultrasound localization microscopy (ULM), obtains blood flow information through plane wave (PW) transmissions at high frame rates. However, low signal-to-no...

HepNet: Deep Neural Network for Classification of Early-Stage Hepatic Steatosis Using Microwave Signals.

IEEE journal of biomedical and health informatics
Hepatic steatosis, a key factor in chronic liver diseases, is difficult to diagnose early. This study introduces a classifier for hepatic steatosis using microwave technology, validated through clinical trials. Our method uses microwave signals and d...

rU-Net, Multi-Scale Feature Fusion and Transfer Learning: Unlocking the Potential of Cuffless Blood Pressure Monitoring With PPG and ECG.

IEEE journal of biomedical and health informatics
This study introduces an innovative deep-learning model for cuffless blood pressure estimation using PPG and ECG signals, demonstrating state-of-the-art performance on the largest clean dataset, PulseDB. The rU-Net architecture, a fusion of U-Net and...

mDARTS: Searching ML-Based ECG Classifiers Against Membership Inference Attacks.

IEEE journal of biomedical and health informatics
This paper addresses the critical need for elctrocardiogram (ECG) classifier architectures that balance high classification performance with robust privacy protection against membership inference attacks (MIA). We introduce a comprehensive approach t...

Interpretable Multi-Branch Architecture for Spatiotemporal Neural Networks and Its Application in Seizure Prediction.

IEEE journal of biomedical and health informatics
Currently, spatiotemporal convolutional neural networks (CNNs) for electroencephalogram (EEG) signals have emerged as promising tools for seizure prediction (SP), which explore the spatiotemporal biomarkers in an epileptic brain. Generally, these CNN...

Acoustic COVID-19 Detection Using Multiple Instance Learning.

IEEE journal of biomedical and health informatics
In the COVID-19 pandemic, a rigorous testing scheme was crucial. However, tests can be time-consuming and expensive. A machine learning-based diagnostic tool for audio recordings could enable widespread testing at low costs. In order to achieve compa...