Latest AI and machine learning research in intensivists for healthcare professionals.
BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approach to identify individuals at risk for heart failure (HF) and guide preventive interventions. OBJECTIVES: The purpose of this study was to assess whether ECG-AI designed to detect systolic and diastolic dysfunction enhances the prediction of incident HF over clinical risk estimation using the PREVENT...
Behavioural Artificial Intelligence Technology (BAIT) has recently been proposed to codify expert reasoning for sepsis surveillance. We provide preliminary cross-institutional data from two Southeast Asian hospitals (NÂ =Â 1042 suspected sepsis episodes), demonstrating challenges in multi-national generalizability, misclassification of non-infectious inflammatory states, and underutilization of proc...
OBJECTIVE: This study has two main objectives: (1) to develop a multi-model framework for predicting Intensive Care Unit (ICU) mortality within the fi...
BACKGROUND: Intensive Care Unit (ICU) nursing is demanding, requiring advanced clinical decision-making and emergency management skills. Simulation-ba...
Anomaly detection is essential in various domains, where identifying rare and irregular samples is critical for system safety and security. This probl...
BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by physical or emotional stress, involving complex multi...
BACKGROUND: Patients with sepsis often exhibit a decrease in lymphatic numbers, which can be facilitated by protein arginine methyltransferase (PRMT)....
BACKGROUND: Neonatal diseases represent the leading cause of death in Nigeria, ranking the country second globally in neonatal mortality rates. Early ...
Multi-modal hashing offers advantages in large-scale multimedia retrieval by integrating multi-modal features and generating compact binary codes for ...
Hospital-acquired pneumonia (HAP) remains the most frequent and lethal hospital acquired infection, driving ICU mortality, prolonged length of stay, a...
Anesthesia is a cornerstone of modern surgical practice, enabling interventions by deliberately modulating nociception and consciousness-from localize...
OBJECTIVES: Early diagnosis of suspected sepsis is crucial to improve patient survival. Cell population (CP) data, a set of leucocyte research paramet...
As a key feedstock for sustainable bioenergy, microalgae require precise regulation of lipid synthesis and accurate detection methods. To efficiently ...
PURPOSE: Landiolol is a beta-blocker used in the treatment of Sepsis. However, how this drug influences key genes and pathways involved in disease rem...
Artificial intelligence (AI) has the potential to revolutionize critical care medicine by enhancing patient care, improving resource allocation and re...
Current machine learning-based (ML) models usually attempt to utilize all available patient data to predict patient outcomes while ignoring the associ...
Surface-enhanced Raman spectroscopy (SERS) is a powerful, label-free technique for pathogen detection; however, its broader adoption in clinical diagn...
Septic shock remains one of the most severe complications of infection, defined by circulatory, cellular, and metabolic dysfunction and associated wit...
Artificial intelligence (AI) has regained strong momentum in medicine, driven by unprecedented computing power and the availability of massive clinica...
OBJECTIVE: Guideline-based recommendations for posthemostasis resuscitation in trauma patients remain limited. This study aimed to define an interpret...