Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Showing 1828-1848 of 7,427 articles
Rapid Assessment of Fish Freshness for Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy and Fusion-Based Artificial Intelligence.

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimod...

Real-Time Kinematically Synchronous Planning for Cooperative Manipulation of Multi-Arms Robot Using the Self-Organizing Competitive Neural Network.

This paper presents a real-time kinematically synchronous planning method for the collaborative mani...

A Convex Optimization Approach to Multi-Robot Task Allocation and Path Planning.

In real-world applications, multiple robots need to be dynamically deployed to their appropriate loc...

NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis.

This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) to s...

The Evolution and Future of Intensive Care Management in the Era of Telecritical Care and Artificial Intelligence.

Critical care practice has been embodied in the healthcare system since the institutionalization of ...

Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions.

There is a growing need to apply geospatial artificial intelligence analysis to disparate environmen...

Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach.

OBJECTIVE: Acute kidney injury (AKI), a common condition on the intensive-care unit (ICU), is charac...

Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis.

Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artif...

AI-Driven sleep staging from actigraphy and heart rate.

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantifica...

Optimal machine learning methods for prediction of high-flow nasal cannula outcomes using image features from electrical impedance tomography.

BACKGROUND: High-flow nasal cannula (HNFC) is able to provide ventilation support for patients with ...

One-Step Robot-Assisted Complete Urinary Tract Extirpation in Man with End-Stage Renal Disease on Dialysis: The First Case Report.

Urothelial carcinoma (UC) could be observed in urinary bladder (UBUC) and upper urinary tracts (UTUC...

Supervised deep learning with vision transformer predicts delirium using limited lead EEG.

As many as 80% of critically ill patients develop delirium increasing the need for institutionalizat...

Enhancing Total Optical Throughput of Microscopy with Deep Learning for Intravital Observation.

The significance of performing large-depth dynamic microscopic imaging in vivo for life science rese...

Artificial Intelligence in Intensive Care Medicine: Toward a ChatGPT/GPT-4 Way?

Although intensive care medicine (ICM) is a relatively young discipline, it has rapidly developed in...

In-Sensor Artificial Intelligence and Fusion With Electronic Medical Records for At-Home Monitoring.

This work presents an artificial intelligence (AI) framework for real-time, personalized sepsis pred...

Human Collective Intelligence Inspired Multi-View Representation Learning - Enabling View Communication by Simulating Human Communication Mechanism.

In real-world applications, we often encounter multi-view learning tasks where we need to learn from...

EgoCom: A Multi-Person Multi-Modal Egocentric Communications Dataset.

Multi-modal datasets in artificial intelligence (AI) often capture a third-person perspective, but o...

AI-Guided Computing Insights into a Thermostat Monitoring Neonatal Intensive Care Unit (NICU).

In any healthcare setting, it is important to monitor and control airflow and ventilation with a the...

A dosing strategy model of deep deterministic policy gradient algorithm for sepsis patients.

BACKGROUND: A growing body of research suggests that the use of computerized decision support system...

Advancing Stuttering Detection via Data Augmentation, Class-Balanced Loss and Multi-Contextual Deep Learning.

Stuttering is a neuro-developmental speech impairment characterized by uncontrolled utterances (inte...

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