Latest AI and machine learning research in pci for healthcare professionals.
Deep vein thrombosis (DVT) in fracture patients is often clinically silent, with a high incidence of thrombosis and associated mortality. Static machine learning methods struggle to address the challenge of early DVT diagnosis due to their inability to adapt to heterogeneous data across patients. In contrast, Dynamic Ensemble Selection (DES) improves clinical decision-making and therapeutic interv...
Acute ischemic stroke (AIS) outcomes depend critically on rapid, accurate early diagnosis in the emergency department. Traditional prehospital tools and large vessel occlusion focused scales aid triage, but have limited ability to distinguish ischemic from hemorrhagic stroke, a distinction essential for treatment decision in acute phase. Recent advances include mobile stroke units equipped with co...
As space exploration advances into the era of deep space exploration, humanity faces unprecedented challenges in maintaining astronaut health, not onl...
BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...
This scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideli...
Adverse events and medication-related errors are common with anticoagulants. Heparin infusions are frequently associated with administration errors or...
OBJECTIVE: To evaluate the agreement of automation tools with expert evaluators in identifying cases meeting inclusion and exclusion criteria for retr...
PURPOSE OF REVIEW: Moyamoya vasculopathy is a progressive cerebrovascular steno-occlusive disease with variable presentation. As revascularization tec...
Exome sequencing (ES) has transformed genomic research and clinical diagnostics by enabling precise identification of disease-associated variants with...
BACKGROUND: Biliary stent placement during endoscopic retrograde cholangiopancreatography (ERCP) is important for drainage in common bile duct (CBD) s...
Digital twin technology, which enables the creation of patient-specific virtual models, is increasingly applied in interventional cardiology to suppor...
BACKGROUND: Minimizing postoperative complications is imperative to improving patient outcomes. The purpose of this investigation is to develop machin...
BACKGROUND: Thrombophilia evaluation requires integration of biochemical findings with clinical history, much of which is embedded in unstructured ele...
BACKGROUND: Timely detection and monitoring of abdominal aortic aneurysms (AAAs) are necessary to prevent ruptures and decrease mortality. Artificial ...
BACKGROUND: Large language models (LLMs) have demonstrated remarkable capabilities in various medical fields, yet their performance in thrombosis and ...
INTRODUCTION: Bleeding is a serious complication in cardiac surgery, especially among patients receiving combined anticoagulant and antiplatelet thera...
PURPOSE: This systematic review evaluates the effectiveness of artificial intelligence (AI) models in dental implant treatment planning, focusing on: ...
BACKGROUND: Tunneled central venous catheters (tCVCs) are essential in hemodialysis when arteriovenous access is not feasible. Their correct positioni...
Venous thromboembolism (VTE) remains a leading cause of cardiovascular morbidity and mortality, despite advances in imaging and anticoagulation. VTE a...
BACKGROUND: Accurate and rapid phenotyping of venous thromboembolism (VTE) in longitudinal studies is important. A natural language processing (NLP) t...