Strokes

Consistency analysis of AI cell recognition results between non anticoagulant and anticoagulant marrow smear after Wright's staining.

The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technology within the medical sector. Despite the current high accuracy of AI in cell identification, there remains a clinical need for fully automated AI cell recognition equipment that spans from sample processing to result generation. The source of the s...

Plasma proteomic profiles reveal proteins and characteristic patterns associated with hypertension: A prospective cohort study.

BACKGROUND: Longitudinal proteomic studies on hypertension remain scarce. We evaluated the epidemiological associations of circulating proteins with hypertension on the basis of the UK Biobank (UKB) and public GWAS-summary data in this study. METHODS: This study included 22 788 participants without hypertension on baseline and 2910 plasma proteins from the UKB. The competing risk regression and Me...

Thrombosis at the crossroads of inflammation, coagulation, and vascular biology: Recent advances and emerging therapeutic strategies.

Thrombosis is a multifaceted pathological process involving intravascular clot formation that drives a range of cardiovascular and cerebrovascular dis...

Can a Large Language Model Grounded in Text-Based Agency-Specific Prehospital Protocols Provide Accurate Care Recommendations?

OBJECTIVES: Large language models (LLMs) using a retrieval-augmented generation (RAG) approach have the ability to respond to user queries with answer...

An upper limb stroke rehabilitation exercise video dataset.

Stroke is one of the leading causes of disability worldwide with a disproportionately high burden in low and middle-income countries. In such countrie...

Improving Readability of Stroke Clinical Trial Consent Forms Using Artificial Intelligence.

BACKGROUND: Informed consent forms (ICFs) for clinical trials are often written above the recommended eighth-grade level. We aimed to compare the read...

Testing Near-Field Radio-Frequency Sensors to Predict Respiratory Distress in Patients Living With Dementia: A Pilot Feasibility and Acceptability Study.

BackgroundPeople living with dementia (PLWD) with advanced illness are prone to respiratory distress yet often cannot self-report dyspnea, delaying re...

Predicting online motor learning after stroke in lower limb task using machine learning.

Online motor learning is central to effective learning and a crucial determinant of functional recovery after stroke. Despite its clinical significanc...

Beyond NIHSS and neuroimaging: an interpretable gradient boosting model for predicting in-hospital mortality in ICU patients with acute ischemic stroke.

This study aimed to develop an interpretable machine learning model for predicting in-hospital mortality among acute ischemic stroke (AIS) patients ad...

Use of Machine-Learning Models to Identify Clinical Features Associated With A Future Clinical Worsening Event in Patients With Pulmonary Arterial Hypertension.

Clinical worsening events are increasingly recognized as a meaningful outcome in pulmonary arterial hypertension (PAH). We applied machine-learning mo...

The presymptomatic and early manifestations of semantic dementia.

People with semantic dementia (SD) or semantic variant primary progressive aphasia typically present with marked atrophy of the anterior temporal lobe...

Prognostic significance of right ventricular myocardial features derived from echocardiography using a deep learning framework in pulmonary arterial hypertension.

BACKGROUND: The function and myocardial characteristics of the right ventricle (RV) are linked to RV dysfunction and prognosis in pulmonary arterial h...

Artificial intelligence-assisted peri-operative echocardiography: a multicentre observational study.

INTRODUCTION: Point-of-care transthoracic echocardiography performed by anaesthetists can influence peri-operative management but is constrained by ti...

Evaluating AI-Enabled Technologies for Atrial Fibrillation Detection: A Systematic Review of Diagnostic Performance.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained arrhythmia worldwide and a major contributor to stroke and cardiovascular morbidity....

Neutrophil extracellular traps-related biomarkers in idiopathic pulmonary arterial hypertension: A machine learning-based identification and experimental validation study.

Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular m...

A novel feedback-based compensation reduction with upper body reconstruction for upper-limb rehabilitation.

Compensatory movements frequently occur during upper-limb rehabilitation for patients with stroke, potentially impeding effective motor recovery. Visi...

Deep Learning Radiomics Signature from Multicontrast MRI for Automated Identification of Symptomatic Carotid Plaques: A Multicenter Study.

BACKGROUND AND PURPOSE: Ischemic stroke poses a significant global health burden. Accurately identifying symptomatic carotid atherosclerotic plaques, ...

Machine learning-based cardiovascular risk prediction in systemic lupus erythematosus: development and internal validation of a prognostic model.

BACKGROUND: Cardiovascular (CV) diseases are the leading cause of mortality in patients with systemic lupus erythematosus (SLE). While traditional ris...

Identification of Mitochondrial Dysfunction Genes as Diagnostic Biomarkers for Ischemic Stroke by Integrated Bioinformatics Analysis and Machine Learning.

Current diagnostics for ischemic stroke (IS) lack timeliness and accessibility, highlighting the need for novel molecular diagnostic models. Three gen...

Effectiveness of Patent Foramen Ovale Occlusion Devices Versus Medical Therapy: An Indirect Comparison Based on Reconstructed Individual Patient Data.

BACKGROUND: Percutaneous closure of patent foramen ovale (PFO) reduces the risk of recurrent stroke in selected patients with cryptogenic stroke. Howe...