Strokes

Learning from Similarity Proportion Loss for Classifying Skeletal Muscle Recovery Stages

Evaluating the regeneration process of damaged muscle tissue is a fundamental analysis in muscle research to measure experimental effect sizes and uncover mechanisms behind muscle weakness due to aging and disease. The conventional approach to assessing muscle tissue regeneration involves whole-slide imaging and expert visual inspection of the recovery stages based on the morphological informati...

Multimodal Deep Learning for Stroke Prediction and Detection using Retinal Imaging and Clinical Data

Stroke is a major public health problem, affecting millions worldwide. Deep learning has recently demonstrated promise for enhancing the diagnosis and risk prediction of stroke. However, existing methods rely on costly medical imaging modalities, such as computed tomography. Recent studies suggest that retinal imaging could offer a cost-effective alternative for cerebrovascular health assessment...

Compositional Image-Text Matching and Retrieval by Grounding Entities

Vision-language pretraining on large datasets of images-text pairs is one of the main building blocks of current Vision-Language Models. While with ...

Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.

INTRODUCTION: Post-stroke depression is one of the important complications of stroke and affects patients' quality of life. Early identification of po...

Evaluating Performance of a Deep Learning Multilabel Segmentation Model to Quantify Acute and Chronic Brain Lesions at MRI after Stroke and Predict Prognosis.

Purpose To develop and evaluate a multilabel deep learning network to identify and quantify acute and chronic brain lesions at multisequence MRI after...

Integrating Artificial Intelligence in the Diagnosis and Management of Metabolic Syndrome: A Comprehensive Review.

BACKGROUND: Metabolic syndrome (MetS) is a progressive chronic pathophysiological state characterised by abdominal obesity, hypertension, hyperglycaem...

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients after continuous-flow left ventricular assist device ...

Artificial intelligence-based echocardiography assessment to detect pulmonary hypertension.

BACKGROUND: Tricuspid regurgitation jet velocity (TRJV) on echocardiography is used for screening patients with suspected pulmonary hypertension (PH)....

Impact of Tagatose on Physicochemical, Nutritional, and In Vitro Digestive Properties of Toast Bread.

It is more attractive to develop effective strategies to reduce sugar intake without compromising food quality with the rising prevalence of obesity a...

Expert consensus document on artificial intelligence of the Italian Society of Cardiology.

Artificial intelligence (AI), a branch of computer science focused on developing algorithms that replicate intelligent behaviour, has recently been us...

GDI-Bench: A Benchmark for General Document Intelligence with Vision and Reasoning Decoupling

The rapid advancement of multimodal large language models (MLLMs) has profoundly impacted the document domain, creating a wide array of application ...

LASHED: LLMs And Static Hardware Analysis for Early Detection of RTL Bugs

While static analysis is useful in detecting early-stage hardware security bugs, its efficacy is limited because it requires information to form che...

A Neural Network for Atrial Fibrillation Detection via PPG.

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with severe complications such as ischemic stroke and heart failure. Early detec...

Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code

Large Language Models (LLMs) have demonstrated significant capabilities in understanding and analyzing code for security vulnerabilities, such as Co...

Distribution-aware Forgetting Compensation for Exemplar-Free Lifelong Person Re-identification

Lifelong Person Re-identification (LReID) suffers from a key challenge in preserving old knowledge while adapting to new information. The existing s...

Enhancing Stroke Diagnosis in the Brain Using a Weighted Deep Learning Approach

A brain stroke occurs when blood flow to a part of the brain is disrupted, leading to cell death. Traditional stroke diagnosis methods, such as CT s...

Beyond Feature Importance: Feature Interactions in Predicting Post-Stroke Rigidity with Graph Explainable AI

This study addresses the challenge of predicting post-stroke rigidity by emphasizing feature interactions through graph-based explainable AI. Post-s...

A Uniform Framework for Handling Position Constraints in String Solving (Technical Report)

We introduce a novel decision procedure for solving the class of position string constraints, which includes string disequalities, not-prefixof, not...

Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage

In this study, hypertension is utilized as an indicator of individual vascular damage. This damage can be identified through machine learning techni...

Going beyond explainability in multi-modal stroke outcome prediction models

Aim: This study aims to enhance interpretability and explainability of multi-modal prediction models integrating imaging and tabular patient data. ...