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Transformer-based heart language model with electrocardiogram annotations.

Scientific reports
This paper explores the potential of transformer-based foundation models to detect Atrial Fibrillation (AFIB) in electrocardiogram (ECG) processing, an arrhythmia specified as an irregular heart rhythm without patterns. We construct a language with t...

VSR-Net: Vessel-Like Structure Rehabilitation Network With Graph Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The morphologies of vessel-like structures, such as blood vessels and nerve fibres, play significant roles in disease diagnosis, e.g., Parkinson's disease. Although deep network-based refinement segmentation and topology-preserving segmentation metho...

Rethinking Copy-Paste for Consistency Learning in Medical Image Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Semi-supervised learning based on consistency learning offers significant promise for enhancing medical image segmentation. Current approaches use copy-paste as an effective data perturbation technique to facilitate weak-to-strong consistency learnin...

Supercapacitor Materials Database Generated using Web Scrapping and Natural Language Processing.

Journal of molecular graphics & modelling
Electrochemical energy storage plays a vital role in achieving environmental sustainability. Supercapacitors emerge as promising alternatives to batteries due to their high-power density and extended lifespan. Extensive scholarly research has been co...

Prediction of mortality risk in critically ill patients with systemic lupus erythematosus: a machine learning approach using the MIMIC-IV database.

Lupus science & medicine
OBJECTIVE: Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE) remains a great challenge in clinical practice. Our study aims to develop and validate predictive models for the mortality risk.

EAMAPG: Explainable Adversarial Model Analysis via Projected Gradient Descent.

Computers in biology and medicine
Despite the outstanding performance of deep learning (DL) models, their interpretability remains a challenging topic. In this study, we address the transparency of DL models in medical image analysis by introducing a novel interpretability method usi...

Gabor-modulated depth separable convolution for retinal vessel segmentation in fundus images.

Computers in biology and medicine
BACKGROUND: In diabetic retinopathy, precise segmentation of retinal vessels is essential for accurate diagnosis and effective disease management. This task is particularly challenging due to the varying sizes of vessels, their bifurcations, and the ...

AI Accelerator With Ultralightweight Time-Period CNN-Based Model for Arrhythmia Classification.

IEEE transactions on biomedical circuits and systems
This work proposes a classification system for arrhythmias, aiming to enhance the efficiency of the diagnostic process for cardiologists. The proposed algorithm includes a naive preprocessing procedure for electrocardiography (ECG) data applicable to...

EDSRNet: An Enhanced Decoder Semantic Recovery Network for 2D Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In recent years, with the advancement of medical imaging technology, medical image segmentation has played a key role in assisting diagnosis and treatment planning. Current deep learning-based medical image segmentation methods mainly adopt encoder-d...

PFPRNet: A Phase-Wise Feature Pyramid With Retention Network for Polyp Segmentation.

IEEE journal of biomedical and health informatics
Early detection of colonic polyps is crucial for the prevention and diagnosis of colorectal cancer. Currently, deep learning-based polyp segmentation methods have become mainstream and achieved remarkable results. Acquiring a large number of labeled ...