AIMC Topic: Respiratory Insufficiency

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Preclinical Evaluation of a New ECCO2R Setup.

ASAIO journal (American Society for Artificial Internal Organs : 1992) Dec 1, 2021
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...
Respiratory Distress Syndrome Humans Carbon Dioxide Adult Extracorporeal Circulation Respiration, Artificial Hypercapnia Child Respiratory Insufficiency
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Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.

British journal of anaesthesia Nov 9, 2021
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...
Models, Theoretical Randomized Controlled Trials as Topic Humans Bias Artificial Intelligence Respiratory Insufficiency Algorithms Research Report Research Design Respiration, Artificial
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Machine learning-based analysis of alveolar and vascular injury in SARS-CoV-2 acute respiratory failure.

The Journal of pathology Mar 30, 2021
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...
Aged, 80 and over Male Respiratory Distress Syndrome Respiratory Insufficiency Vascular System Injuries COVID-19 Female SARS-CoV-2 Aged Humans Machine Learning
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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 Feb 10, 2021
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...
Humans Machine Learning COVID-19 Retrospective Studies Logistic Models Male Triage Middle Aged Emergency Service, Hospital Respiration, Artificial Intubation, Intratracheal Respiratory Insufficiency Female Hospitals Early Warning Score ROC Curve Patient Admission Clinical Decision Rules SARS-CoV-2 Hospitalization Aged
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Identification of biological correlates associated with respiratory failure in COVID-19.

BMC medical genomics Dec 11, 2020
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.
Humans COVID-19 Female SARS-CoV-2 Male Gene Ontology Genome-Wide Association Study Polymorphism, Single Nucleotide Italy Respiratory Insufficiency Spain
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Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia-Challenges, strengths, and opportunities in a global health emergency.

PloS one Nov 12, 2020
AIMS: The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia.
Pneumonia, Viral COVID-19 Prospective Studies Computer Simulation Female SARS-CoV-2 Humans Italy Machine Learning Coronavirus Infections Pandemics Aged Respiratory Insufficiency Male Blood Gas Analysis Middle Aged Betacoronavirus Respiration, Artificial Models, Statistical
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Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial.

Computers in biology and medicine Aug 6, 2020
BACKGROUND: Currently, physicians are limited in their ability to provide an accurate prognosis for COVID-19 positive patients. Existing scoring systems have been ineffective for identifying patient decompensation. Machine learning (ML) may offer an ...
COVID-19 Drug Treatment Clinical Laboratory Techniques Betacoronavirus Pneumonia, Viral Sensitivity and Specificity Male Middle Aged Respiration, Artificial Computational Biology United States Triage Coronavirus Infections Female Respiratory Insufficiency SARS-CoV-2 COVID-19 Testing COVID-19 Humans Aged Algorithms Machine Learning Aged, 80 and over Prospective Studies Pandemics Adult Prognosis
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Predicting respiratory failure after pulmonary lobectomy using machine learning techniques.

Surgery Jul 15, 2020
BACKGROUND: When pulmonary complications occur, postlobectomy patients have a higher mortality rate, increased length of stay, and higher readmission rates. Because of a lack of high-quality consolidated clinical data, it is challenging to assess and...
Humans Machine Learning Middle Aged Risk Assessment Postoperative Complications Lung Adolescent Pneumonectomy Aged, 80 and over Clinical Decision-Making Respiratory Insufficiency Young Adult Female Adult Risk Factors Sensitivity and Specificity Aged Male
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Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Cell May 4, 2020
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are ...
Pilot Projects Cohort Studies Radiologists COVID-19 Models, Biological Humans Coronavirus Infections Respiratory Insufficiency Prognosis Artificial Intelligence Datasets as Topic Tomography, X-Ray Computed Pandemics Pneumonia, Viral Lung China
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Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A better EMR would provide concise, context sensitive patient data, but doing so entails the difficult task of knowing which data are relevant. To determin...
Medical Records Systems, Computerized Humans Machine Learning Physicians Acute Kidney Injury Electronic Health Records Intensive Care Units User-Computer Interface Respiratory Insufficiency Diagnostic Tests, Routine Information Seeking Behavior
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