Critical Care

PEEP guided by electrical impedance tomography during one-lung ventilation in elderly patients undergoing thoracoscopic surgery.

BACKGROUND: To examine the influence of positive end-expiratory pressure (PEEP) settings on lung mechanics and oxygenation in elderly patients undergoing thoracoscopic surgery.

Successful Resuscitation of a Young Girl Who Drank Rivastigmine With Respiratory Failure.

Rivastigmine is a non-competitive reversible inhibitor of acetylcholinesterase which is approved as one of the fi rst-line treatment options for Alzheimer's disease. We present the case of a 33-year-old woman with acute cholinergic syndrome secondary to deliberate rivastigmine poisoning. The patient presented at the emergency department (ED) with drowsy consciousness, dizziness, vomiting, diarrhea...

Predicting weaning difficulty for planned extubation patients with an artificial neural network.

This study aims to construct a neural network to predict weaning difficulty among planned extubation patients in intensive care units.This observation...

A Double-Blind, Randomized Control Trial of Rapidly Infused High Strong Ion Difference (SID) Fluid Versus Hartmann's Solution on Acid-Base Status in Sepsis Patients in the Emergency Department.

BACKGROUND: Balanced fluids are preferred in initial resuscitation of septic patients based on several recent studies. The Stewart's concept on acid-b...

Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical Practice.

Frequent utilization of the Intensive Care Unit (ICU) is associated with higher costs and decreased availability for patients who urgently need it. Co...

Prospect of using deep learning for predicting differentiation of myeloid progenitor cells after sepsis.

Comparing Machine Learning Algorithms for Predicting Acute Kidney Injury.

Prior studies have used vital signs and laboratory measurements with conventional modeling techniques to predict acute kidney injury (AKI). The purpos...

Sleep Apnea Severity Estimation from Respiratory Related Movements Using Deep Learning.

Sleep apnea is a common chronic respiratory disorder which occurs due to the repetitive complete or partial cessations of breathing during sleep. The ...

A Comparison of SVM and CNN-LSTM Based Approach for Detecting Smoke Inhalations from Respiratory signal.

Wearable sensors have successfully been used in recent studies to monitor cigarette smoking events and analyze people's smoking behavior. Respiratory ...

Assessment of an ensemble of machine learning models toward abnormality detection in chest radiographs.

Respiratory diseases account for a significant proportion of deaths and disabilities across the world. Chest X-ray (CXR) analysis remains a common dia...

Reckoning respiratory signals to affectively decipher mental state.

Recognizing mental states from physiological signal is a concern not only for medical diagnostics, but also for cognitive science, behavioral studies ...

RespNet: A deep learning model for extraction of respiration from photoplethysmogram.

Respiratory ailments afflict a wide range of people and manifests itself through conditions like asthma and sleep apnea. Continuous monitoring of chro...

Inverting the Turing Test - Machine Learning to Detect Cognition in the ICU.

[Research on algorithms for identifying the severity of acute respiratory distress syndrome patients based on noninvasive parameters].

Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diag...

Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach.

Obstructive sleep apnea (OSA) is a common sleep-related respiratory disease that affects people's health, especially in the elderly. In the traditiona...

[Application of recurrent neural network in prognosis of peritoneal dialysis].

OBJECTIVE: Deep learning models, including recurrent neural network (RNN) and gated recurrent unit (GRU), were used to construct the clinical prognost...

New Phenotypes for Sepsis: The Promise and Problem of Applying Machine Learning and Artificial Intelligence in Clinical Research.

Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model.

Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was t...

A Multi-View Deep Learning Framework for EEG Seizure Detection.

The recent advances in pervasive sensing technologies have enabled us to monitor and analyze the multi-channel electroencephalogram (EEG) signals of e...

Dynamic Features Impact on the Quality of Chronic Heart Failure Predictive Modelling.

We study the way dynamics affects modelling in chronic heart failure (CHF) tasks. By dynamics we understand the patient history and the appearance of ...