AIMC Topic: Respiratory Insufficiency

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Machine learning predicts acute respiratory failure in pancreatitis patients: A retrospective study.

International journal of medical informatics
PURPOSE: The purpose of the research is to design an algorithm to predict the occurrence of acute respiratory failure (ARF) in patients with acute pancreatitis (AP).

Multicentre validation of a machine learning model for predicting respiratory failure after noncardiac surgery.

British journal of anaesthesia
BACKGROUND: Postoperative respiratory failure is a serious complication that could benefit from early accurate identification of high-risk patients. We developed and validated a machine learning model to predict postoperative respiratory failure, def...

An implantable soft robotic ventilator augments inspiration in a pig model of respiratory insufficiency.

Nature biomedical engineering
Severe diaphragm dysfunction can lead to respiratory failure and to the need for permanent mechanical ventilation. Yet permanent tethering to a mechanical ventilator through the mouth or via tracheostomy can hinder a patient's speech, swallowing abil...

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BMC pulmonary medicine
BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accur...

Preclinical Evaluation of a New ECCO2R Setup.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Low flow extracorporeal carbon dioxide removal (ECCO2R) is a promising approach to correct hypercapnic lung failure, facilitate lung protective ventilation in acute respiratory distress syndrome and to possibly prevent the application of invasive ven...

Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.

British journal of anaesthesia
BACKGROUND: Artificial intelligence (AI) has the potential to personalise mechanical ventilation strategies for patients with respiratory failure. However, current methodological deficiencies could limit clinical impact. We identified common limitati...

Machine learning-based analysis of alveolar and vascular injury in SARS-CoV-2 acute respiratory failure.

The Journal of pathology
Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pneumopathy is characterized by a complex clinical picture and heterogeneous pathological lesions, both involving alveolar and vascular components. The severity and distribution of morpholo...

A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Predicting early respiratory failure due to COVID-19 can help triage patients to higher levels of care, allocate scarce resources, and reduce morbidity and mortality by appropriately monitoring and treating the patients at greatest risk f...

Identification of biological correlates associated with respiratory failure in COVID-19.

BMC medical genomics
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global public health concern. Recently, a genome-wide association study (GWAS) was performed with participants recruited from Italy and Spain by an international consortium group.