Latest AI and machine learning research in strokes for healthcare professionals.
Predicting long-term functional outcomes for individuals with stroke is a significant challenge. Solving this challenge will open new opportunities for improving stroke management by informing acute interventions and guiding personalized rehabilitation strategies. The location of the stroke is a key predictor of outcomes, yet no clinically deployed tools incorporate lesion location information for...
Hypertension is a major risk factor for cardiovascular diseases. This study proposes a novel hypertension screening framework based on awake-sleep differences in photoplethysmography (PPG) indices, using machine learning. We hypothesised that normotensive individuals exhibit greater PPG variation between awake and sleep states than unmanaged hypertensive individuals. The Aurora-BP dataset (n=180; ...
Target Trial Emulation (TTE) has emerged as a rigorous framework for causal inference using observational data, but its application in hypertension re...
Post-stroke aphasia is a major contributor to language impairment and neuro-disability worldwide, making automated assessment a critical research prio...
Understanding the relevance of covert cerebrovascular disease (CCD) for later health will allow clinicians to more effectively monitor and target inte...
Adherence to oral anticoagulants (OACs) for atrial fibrillation (AF) stroke prevention is traditionally defined as taking 80% of doses as prescribed, ...
Magnetic Resonance Diffusion-Weighted Imaging (DWI) is a crucial tool for diagnosing acute ischemic stroke, yet some patients present as DWI-negative....
With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs), including hypertension and diabetes, pose signi...
Large Language Models (LLMs) offer promising applications in healthcare, including drafting referral letters. However, access to LLMs specifically des...
Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (PCI) remains a clinical challenge. Current risk st...
In cardiovascular magnetic resonance (CMR), myocardial native T1 mapping enables quantitative, non-invasive tissue characterization and is sensitive t...
Stroke care generates vast free-text records that slow chart review and hamper data reuse. Large language models (LLMs) have been trialed as a remedy ...
Medication non-adherence remains a significant challenge in managing chronic conditions like diabetes and hypertension, leading to increased morbidity...
Recent advances in the treatment of acute ischemic stroke contribute to improved patient outcomes, yet the mechanisms driving long-term disease trajec...
Although artificial intelligence–enhanced electrocardiography (AI-ECG) has shown promise in detecting cardiac abnormalities, large-scale validation ag...
Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks...
Postoperative atrial fibrillation (PoAF) is known as common coronary artery bypass grafting (CABG) complication. Despite its association with increase...
Post-stroke pain (PSP) affects nearly half of stroke survivors, severely compromising quality of life. The causes of PSP remain underexplored, althoug...
Stroke is one of the leading causes of death and long-term disability globally. Several studies have investigated the incidence and predictors of stro...
Individuals with left-hemisphere damage (LHD), right-hemisphere damage (RHD), dementia, mild cognitive impairment (MCI), traumatic brain injury (TBI),...