A5018269384- Atrial Fibrillation Management and Outcomes
- Neuroscience of respiration and sleep
- Artificial Intelligence in Healthcare
- Cardiovascular Function and Risk Factors
- Chronic Disease Management Strategies
- Cardiac Arrhythmias and Treatments
- Venous Thromboembolism Diagnosis and Management
- Respiratory Support and Mechanisms
- Blood Pressure and Hypertension Studies
- Heart Rate Variability and Autonomic Control
- Artificial Intelligence in Healthcare and Education
- Advanced Data Processing Techniques
- Obstructive Sleep Apnea Research
- Cardiac Structural Anomalies and Repair
- Healthcare Systems and Public Health
- Quality and Safety in Healthcare
- Heart Failure Treatment and Management
- Cardiac Valve Diseases and Treatments
- Infective Endocarditis Diagnosis and Management
- Cardiac pacing and defibrillation studies
- Sleep and Wakefulness Research
- ECG Monitoring and Analysis
- Cardiovascular and exercise physiology
- Neurological Disorders and Treatments
- Cardiac Imaging and Diagnostics
University of Birmingham
2016-2024
University Hospitals Birmingham NHS Foundation Trust
2021-2024
Queen Elizabeth Hospital
2022-2024
NIHR Birmingham Biomedical Research Centre
2024
Evolved Analytics (United States)
2024
Health Data Research UK
2022
Artificial intelligence (AI) is increasingly being utilized in healthcare. This article provides clinicians and researchers with a step-wise foundation for high-value AI that can be applied to variety of different data modalities. The aim improve the transparency application methods, potential benefit patients routine cardiovascular care. Following clear research hypothesis, an AI-based workflow begins selection pre-processing prior analysis, type (structured, semi-structured, or...
Abstract Background and Aims The role of gender in decision-making for oral anticoagulation patients with atrial fibrillation (AF) remains controversial. Methods population cohort study used electronic healthcare records 16 587 749 from UK primary care (2005–2020). Primary (composite all-cause mortality, ischaemic stroke, or arterial thromboembolism) secondary outcomes were analysed using Cox hazard ratios (HR), adjusted age, socioeconomic status, comorbidities. Results 78 852 included AF,...
The prevention of thromboembolism in atrial fibrillation (AF) is typically restricted to patients with specific risk factors and ignores outcomes such as vascular dementia. This population-based cohort study used electronic healthcare records from 5,199,994 primary care (UK; 2005-2020). A total 290,525 (5.6%) had a diagnosis AF were aged 40-75 years, which 36,340 no history stroke, low perceived stroke based on clinical oral anticoagulant prescription. Matching was performed for age, sex...
Improving the efficiency of clinical trials is key to their continued importance in directing evidence-based patient care. Digital innovations, particular use electronic healthcare records (EHRs), allow for large-scale screening and follow up participants. However, it critical these developments are accompanied by robust transparent methods that can support high-quality high value research.
Introduction The echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification patients with heart failure (HF). Methods This paper aimed quantify LVEF automatically accurately proposed pipeline method based on deep neural networks ensemble learning. Within pipeline, an Atrous Convolutional Neural Network (ACNN) was first trained segment ventricle (LV), before employing area-length formulation ellipsoid single-plane model...
Abstract Aims The aim is to describe the rationale, design, delivery, and baseline characteristics of Stroke prevention rhythm control Treatment: Evaluation an Educational programme European society cardiology in a cluster-Randomized trial patients with Atrial Fibrillation (STEEER-AF) trial. Methods results STEEER-AF pragmatic designed objectively robustly determine whether guidelines are adhered routine practice evaluate targeted educational for healthcare professionals. Seventy centres...
ABSTRACT Background Improving the efficiency of clinical trials is key to their continued importance in directing evidence-based patient care. Digital innovations, particular use electronic healthcare records (EHR), allow for large-scale screening and follow-up participants. However, it critical these developments are accompanied by robust transparent methods that can support high quality value research. Methods The DaRe2THINK trial includes a series novel processes, including nationwide...
The echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification patients with heart failure (HF). In order quantify LVEF automatically accurately, this paper proposes a new pipeline method based on deep neural networks ensemble learning. Within pipeline, an Atrous Convolutional Neural Network (ACNN) was first trained segment ventricle (LV), before employing area-length formulation ellipsoid single-plane model calculate values....
Hypoglycaemia (HG) evokes a counter‐regulatory response to restore arterial blood glucose levels. Additionally, HG has also been shown evoke an increase in ventilation whilst maintaining normocapnia suggesting the remained matched metabolism. Whilst it that induces CO 2 sensitivity, there is lack of data on how may modulate pattern breathing normoxia as well during chemoreceptor‐mediated responses. Whole body plethysmography (WBP) allows measurement respiratory variables conscious...
<h3>Background</h3> Thromboembolism in patients with atrial fibrillation (AF) can be prevented, however oral anticoagulation is typically reserved for older or those specific historical comorbidities. Risk scores are widespread use, but limited predictive accuracy stroke and no consideration of current major challenges such as dementia. This study provides contemporary data on the risk thromboembolism, including both cardiac cerebral damage. <h3>Methods</h3> Population-based matched cohort...