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CAPI-Detect: machine learning in capillaroscopy reveals new variables influencing diagnosis.

Rheumatology (Oxford, England)
OBJECTIVES: Nailfold videocapillaroscopy (NVC) is the gold standard for diagnosing SSc and differentiating primary from secondary RP. The CAPI-Score algorithm, designed for simplicity, classifies capillaroscopy scleroderma patterns (CSPs) using a lim...

Deep learning-enhanced zero echo time MRI for glenohumeral assessment in shoulder instability: a comparative study with CT.

Skeletal radiology
PURPOSE: To evaluate image quality and lesion conspicuity of zero echo time (ZTE) MRI reconstructed with deep learning (DL)-based algorithm versus conventional reconstruction and to assess DL ZTE performance against CT for bone loss measurements in s...

Development and validation of the Open-Source Automatic Bowel Preparation Scale.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Insufficient bowel preparation accounts for up to 42% of missed adenomas in colonoscopy. However, major analysis programs found no correlation between adenoma detection rate and the human-rated Boston Bowel Preparation Scale (BBP...

The impact of AI-based decision support systems on nursing workflows in critical care units.

International nursing review
AIM: This research examines the effects of artificial intelligence (AI)-based decision support systems (DSS) on the operational processes of nurses in critical care units (CCU) located in Amman, Jordan.

Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects.

Pediatric cardiology
Secundum atrial septal defect (ASD2) detection is often delayed, with the potential for late diagnosis complications. Recent work demonstrated artificial intelligence-enhanced ECG analysis shows promise to detect ASD2 in adults. However, its applicat...

Deep-learning based multi-modal models for brain age, cognition and amyloid pathology prediction.

Alzheimer's research & therapy
BACKGROUND: Magnetic resonance imaging (MRI), combined with artificial intelligence techniques, has improved our understanding of brain structural change and enabled the estimation of brain age. Neurodegenerative disorders, such as Alzheimer's diseas...

Machine learning algorithms to predict stroke in China based on causal inference of time series analysis.

BMC neurology
IMPORTANCE: Identifying and managing high-risk populations for stroke in a targeted manner is a key area of preventive healthcare.

Enhanced neuroplasticity and gait recovery in stroke patients: a comparative analysis of active and passive robotic training modes.

BMC neurology
BACKGROUND: Stroke is a leading cause of long-term disability, with lower limb dysfunction being a common sequela that significantly impacts patients' mobility and quality of life. Robotic-assisted training has emerged as a promising intervention for...