Latest AI and machine learning research in critical care for healthcare professionals.
PURPOSE OF REVIEW: Medical devices like physiologic monitors, anesthesia machines, and ventilators, are designed by biomedical engineers but used by clinicians. Advanced medical technology can be incorporated into clinical practice safely, but addressing alarm fatigue, resilience, automation complacency, and clinician wellbeing will help to maintain and improve patient safety. RECENT FINDINGS: The...
Sepsis is a life-threatening condition that can be fatal. Advances in big data analytics and the data-rich environment of intensive care units have enabled the development of artificial intelligence-based early warning systems that offer a solution to reduce sepsis-related mortality. Support Vector Machines (SVMs) establish optimal classifiers and deep learning automatically learns key features. T...
BACKGROUND: Viral communities of the upper aerodigestive tract represent an important component of the human microbial ecosystem but remain poorly cha...
Postoperative delirium (POD) is a common perioperative complication involving central nervous system dysfunction, particularly among critically ill an...
The proliferation of Internet of Things (IoT) devices in smart home environments has dramatically expanded the attack surface for cyber threats, parti...
Accurate short-term ozone (O3) forecasting is critical for mitigating respiratory and ecological impacts, protecting public health, and guiding urban ...
We aimed to systematically analyze the historical evolution of artificial intelligence (AI) in end-stage renal disease (ESRD) management and propose a...
Graphical abstracts are increasingly used to enhance scientific communication, yet their quality remains variable. Generative artificial intelligence ...
Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of ...
OBJECTIVES: Lymphoma is a prevalent hematologic malignancy with complex pathogenesis involving dysregulated signaling pathways and high treatment resi...
BACKGROUND/AIM: Risky alcohol use is common among university students and negatively impacts physical and psychosocial health. Current screening instr...
BACKGROUND: Artificial intelligence (AI) is reshaping clinical decision support systems (CDSSs). In acute and critical care, nurses provide continuous...
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are emerging as transformative tools in healthcare, with significant potential to e...
BACKGROUND: Pulmonary ventilation imaging has become an increasingly important component in thoracic radiotherapy, as it is applied to functional avoi...
Introduction: Electrical impedance tomography (EIT) is a noninvasive, radiation-free imaging modality that provides real-time information on regional ...
BACKGROUND: Emergency departments (EDs) operate under time pressure, diagnostic uncertainty, and cognitive overload. Artificial intelligence (AI)-driv...
OBJECTIVES: Snoring is a major acoustic manifestation of upper airway obstruction and an indicator of sleep-disordered breathing (SDB). However, objec...
BACKGROUND AND OBJECTIVES: Hypertrophic Cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy. Its left ventricular hypertrophy (LVH) ph...
Colorectal cancer (CRC) remains a leading cause of cancer mortality globally, with therapeutic efficacy hindered by tumor heterogeneity and drug resis...
Early sepsis detection is essential for improving outcomes and reducing costs, but traditional rule-based systems have limited accuracy and real-world...