Latest AI and machine learning research in critical care for healthcare professionals.
BACKGROUND: Early diagnosis of acute kidney injury (AKI) is a major challenge in the intensive care unit (ICU). The AKIpredictor is a set of machine-learning-based prediction models for AKI using routinely collected patient information, and accessible online. In order to evaluate its clinical value, the AKIpredictor was compared to physicians' predictions.
In this letter, we propose two novel methods for four-class motor imagery (MI) classification using electroencephalography (EEG). Also, we developed a real-time health 4.0 (H4.0) architecture for brain-controlled internet of things (IoT) enabled environments (BCE), which uses the classified MI task to assist disabled persons in controlling IoT-enabled environments such as lighting and heating, ven...
BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preterm infants due to the potential for the adhesive el...
To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and allied-conditions (COPDAC) using a multi domain a...
OBJECTIVE: The neonatal period of a child is considered the most crucial phase of its physical development and future health. As per the World Health ...
Grading spondylolisthesis into several stages from MRI images is challenging because detecting critical vertebrae and locating landmarks in images of ...
BACKGROUND: Kidney transplantation should improve abnormalities that are common during dialysis treatment, like anaemia and mineral and bone disorder....
OBJECTIVES: To provide proof-of-concept for a protocol applying a strategy of personalized mechanical ventilation in children with acute respiratory d...
BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency of 29% of deceased donor renal transplantation (DD...
This article investigates the classification of normal and COPD subjects on the basis of respiratory sound analysis using machine learning techniques....
OBJECTIVE: Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; ...
BACKGROUND: This study aims to investigate the effect of ventilation of the non-ventilated lung in patients undergoing one-lung ventilation by a separ...
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time req...
BACKGROUND: Doppler ultrasound (DU) monitoring early after arteriovenous fistula (AVF) creation allows the identification of low blood flow (Qa) requi...
Currently, many critical care indices are not captured automatically at a granular level, rather are repetitively assessed by overburdened nurses. In ...
The neuronal multiunit model presented here is a formal model of the central pattern generator (CPG) of the amphibian ventilatory neural network, insp...
BACKGROUND AND OBJECTIVE: Monitoring of changes in respiratory rate provides information on a patient's psychophysical state. This paper presents a re...
Estimating hospital mortality of patients is important in assisting clinicians to make decisions and hospital providers to allocate resources. This pa...
BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis patients after fluid resuscitation.