Critical Care

Detection of respiratory rate using a classifier of waves in the signal from a FBG-based vital signs sensor.

BACKGROUND AND OBJECTIVE: Monitoring of changes in respiratory rate provides information on a patien...

Is artificial intelligence (AI) at the doorstep of Intensive Care Units (ICU) and operating room (OR)?

A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascula...

Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.

BACKGROUND AND OBJECTIVE: Fraction of Inspired Oxygen is one of the arbitrary set ventilator paramet...

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning sy...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's disco...

Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests.

The interpretation of pulmonary function tests (PFTs) to diagnose respiratory diseases is built on e...

Towards real-time respiratory motion prediction based on long short-term memory neural networks.

Radiation therapy of thoracic and abdominal tumors requires incorporating the respiratory motion int...

An Equation Based on Fuzzy Mathematics to Assess the Timing of Haemodialysis Initiation.

In order to develop an equation that integrates multiple clinical factors including signs and sympto...

Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units.

BACKGROUND: Reinforcement learning (RL) provides a promising technique to solve complex sequential d...

Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs...

Intensive Care Unit Telemedicine in the Era of Big Data, Artificial Intelligence, and Computer Clinical Decision Support Systems.

This article examines the history of the telemedicine intensive care unit (tele-ICU), the current st...

Heterogeneous effects of alveolar recruitment in acute respiratory distress syndrome: a machine learning reanalysis of the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial.

BACKGROUND: Despite a robust physiological rationale, recruitment manoeuvres with PEEP titration wer...

Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

This study focuses on identifying environmental health risk factors related to acute respiratory dis...

Machine learning for patient risk stratification for acute respiratory distress syndrome.

BACKGROUND: Existing prediction models for acute respiratory distress syndrome (ARDS) require manual...

Expert-level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks.

First and second ventilatory thresholds (VT and VT) represent the boundaries of the moderate-heavy a...

Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network.

PURPOSE: Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analy...

Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework.

Emotional arousal often facilitates memory for some aspects of an event while impairing memory for o...

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

OBJECTIVE: Obstructive sleep-disordered breathing (SDB) events, unlike central events, are associate...

Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

BACKGROUND: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagn...

Noninvasive prediction of Blood Lactate through a machine learning-based approach.

We hypothesized that blood lactate concentration([Lac]) is a function of cardiopulmonary variables, ...