Latest AI and machine learning research in critical care for healthcare professionals.
In recent years, artificial intelligence (AI) has become an increasingly prominent player in emergency medicine, offering innovative tools to enhance the early diagnosis of acute conditions. This systematic review explores how AI, particularly through machine learning (ML) and deep learning (DL), is transforming the way physicians and healthcare professionals respond to high-stakes clinical scenar...
BACKGROUND: Sepsis is common and deadly, and subtypes are proposed to guide precision treatment. However, little is known about the uncertainty in subtype classification, and its implications for trajectory and treatment response. METHODS: In multiple electronic health record and trial data of adults with sepsis, we assigned patients clinical sepsis subtypes (α, β, γ, or δ-type), and measured unce...
BACKGROUND: The complexity of many AI models hinders their clinical adoption because the clinicians using them do not regard them as transparent. This...
BACKGROUND: Elderly acute pancreatitis (AP) patients face significantly higher in-hospital all-cause mortality, highlighting the need for effective ri...
PURPOSE: Respiratory motion (RM)-related artifacts significantly impact image quality and diagnostic accuracy in PET/CT imaging. This study aimed to p...
Staphylococcus aureus is a leading cause of nosocomial infections, including sepsis, bacteraemia, pneumonia, and endocarditis, and continues to pose a...
Chronic kidney disease (CKD) is a leading cause of death worldwide. Currently available drugs slow but do not cure or prevent progression to end-stage...
BACKGROUND: Elective surgical admissions form a growing share of demand for ICU beds, a constrained resource. Capacity planning for these admissions i...
Myelosuppression is a common secondary manifestation of sepsis and is associated with increased morbidity and mortality. Recent evidence suggests that...
Electronic health records (EHRs) capture evolving physiological processes, yet most machine learning models impose static or sequential assumptions th...
Pedestrian safety remains a critical global concern, especially in countries like India, where unsignalized crossings with limited traffic control con...
BACKGROUND: Rapid global aging has led to an increasing demand for long-term care services for the elderly; however, current long-term care systems ar...
OBJECTIVE: The computed tomography-severity score (CT-SS) quantifies the severity of pulmonary involvement and is significantly associated with diseas...
The immune defense function protecting the body from invasive pathogens is a key indicator of an individual's health and lacks of methods for quantita...
BACKGROUND: Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is ste...
Metals in PM2.5 are closely associated with cardiopulmonary disease endpoints, potentially attributable to ionic species-induced oxidative stress effe...
Evaluating chemical toxicity and its potential hazards to human health and the environment is essential in diverse fields, including medicine, industr...
BACKGROUND AND OBJECTIVE: Aircraft pilots can be faced with a high mental workload (MW) combined with moderate hypoxia and sleep restriction. We aimed...
OBJECTIVE: To overcome critical limitations of B-mode ultrasound in artificial intelligence diagnostics-including poor image quality and operator vari...