Intensivists

Tunable Plug-and-Play Meta-Nanogenerator Materials for Multi-Range Force Measurements.

Accurate assessments of mechanical forces are crucial for the design, operation and maintenance of long-lasting engineering systems. Conventional force sensors that are deployed in engineering applications suffer from multiple shortcomings including high power consumption, poor integrability, costly, limited force sensing ranges and lack multifunctionality. In this study, we present a fully integr...

Lifespan Pancreas Morphology for Control Versus Type 2 Diabetes Using AI on Largescale Clinical Imaging.

Understanding how pancreas size and shape change with normal aging is critical for establishing a baseline to detect deviations in type 2 diabetes and other pancreatic disease. We measure pancreas size and shape using morphological measurements from early development through aging (ages 0-90). Our goals are to (1) identify reliable clinical imaging modalities for artificial intelligence (AI) based...

Goals of Care Transitions following Postoperative Undertriage.

BACKGROUND: This study tests the hypothesis that postoperative undertriage of high-acuity patients to hospital floor units is associated with new post...

Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba Networks.

Sepsis-associated acute kidney injury (SA-AKI) is a heterogeneous clinical syndrome and a leading cause of mortality in intensive care units (ICUs). I...

An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study.

Sepsis is a major global health crisis where early recognition and effective management remain significant challenges for healthcare systems. As part ...

Quality and Reliability of AI Information on Dental Implant Failure: A Comparative Multi-Model Analysis.

OBJECTIVE: This study aimed to develop a consensus-based set of patient questions on dental implant failure and to compare the clarity, quality, accur...

Artificial intelligence for early diagnosis in emergency department.

In recent years, artificial intelligence (AI) has become an increasingly prominent player in emergency medicine, offering innovative tools to enhance ...

Fuzzy classification of sepsis subtypes and implications for trajectory and treatment.

BACKGROUND: Sepsis is common and deadly, and subtypes are proposed to guide precision treatment. However, little is known about the uncertainty in sub...

Clinician preferences for explainable AI in critical care: a comparative study of interpretable models and visualizations for intubation decision support.

BACKGROUND: The complexity of many AI models hinders their clinical adoption because the clinicians using them do not regard them as transparent. This...

A novel hypothetical protein (SAUSA300_1684) confers excellent protection against multi-drug-resistant Staphylococcus aureus infection in the murine model.

Staphylococcus aureus is a leading cause of nosocomial infections, including sepsis, bacteraemia, pneumonia, and endocarditis, and continues to pose a...

Development of a machine learning model to predict intensive care unit bed demand for adult elective surgical patients at a large United Kingdom National Health Service Trust.

BACKGROUND: Elective surgical admissions form a growing share of demand for ICU beds, a constrained resource. Capacity planning for these admissions i...

Learning-Based Multi-View Stereo: A Survey.

3D reconstruction aims to recover the dense 3D structure of a scene. It plays an essential role in various applications such as Augmented/Virtual Real...

Dataset-centric evaluation of federated intrusion detection models in IoT networks.

Intrusion detection systems (IDS) leveraging federated learning (FL) are increasingly deployed in Internet of Things (IoT) environments to address dis...

Plasma glutamic acid predicts myelosuppression and mortality in septic patients using machine learning.

Myelosuppression is a common secondary manifestation of sepsis and is associated with increased morbidity and mortality. Recent evidence suggests that...

Lactate to albumin ratio predicts one year mortality in ICU patients receiving invasive mechanical ventilation.

The lactate-to-albumin ratio (LAR), a composite biomarker reflecting both inflammatory burden and nutritional status, has been associated with adverse...

Construction of a classification system for long-term care service needs among the elderly based on cluster analysis and machine learning: A multi-center, cross-sectional study in central China.

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...

Prognostic Significance of Computed Tomography Severity Score for Machine Learning Prediction of Intensive Care Unit Admission in COVID-19 Patients.

OBJECTIVE: The computed tomography-severity score (CT-SS) quantifies the severity of pulmonary involvement and is significantly associated with diseas...

A Deep Representation Learning Method for Quantitative Immune Defense Function Evaluation and Its Clinical Applications.

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...

Optimizing wastewater treatment through combined deep learning and deep reinforcement learning: Recent advances and future prospects.

Wastewater treatment plants (WWTPs) are critical components of urban infrastructure, and enhancing their performance while reducing carbon emissions i...

Artificial Intelligence Monitoring of Neurological Status From Patient Videos in the Neuroscience Intensive Care Unit.

BACKGROUND AND OBJECTIVES: The neurological examination is pivotal in assessing patients with neurological conditions but has severe limitations: It c...