e-learning
resources
Virtual 2021
05.09.2021
COVID-19 and acute respiratory failure
Login
Search all ERS
e-learning
resources
Disease Areas
Airways Diseases
Interstitial Lung Diseases
Respiratory Critical Care
Respiratory Infections
Paediatric Respiratory Diseases
Pulmonary Vascular Diseases
Sleep and Breathing Disorders
Thoracic Oncology
Events
International Congress
Courses
Webinars
Conferences
Research Seminars
Journal Clubs
Publications
Breathe
Monograph
ERJ
ERJ Open Research
ERR
European Lung White Book
Handbook Series
Guidelines
All ERS guidelines
e-learning
CME Online
Case reports
Short Videos
SpirXpert
Procedure Videos
CME tests
Reference Database of Respiratory Sounds
Radiology Image Challenge
Brief tobacco interventions
EU Projects
VALUE-Dx
ERN-LUNG
ECRAID
UNITE4TB
Disease Areas
Events
Publications
Guidelines
e-learning
EU Projects
Login
Search
Using Machine Learning to Predict mortality for first-day COVID-19 patients presenting to the ICU
E. Jamshidi (Lausanne, Switzerland), S. Rahi (Lausanne, Switzerland), N. Mansouri (Lausanne, Switzerland)
Source:
Virtual Congress 2021 – COVID-19 and acute respiratory failure
Session:
COVID-19 and acute respiratory failure
Session type:
E-poster
Number:
901
Rating:
You must
login
to grade this presentation.
Share or cite this content
Citations should be made in the following way:
E. Jamshidi (Lausanne, Switzerland), S. Rahi (Lausanne, Switzerland), N. Mansouri (Lausanne, Switzerland). Using Machine Learning to Predict mortality for first-day COVID-19 patients presenting to the ICU. 901
You must
login
to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.
Member's Comments
No comment yet.
You must
Login
to comment this presentation.
Related content which might interest you:
The Relationship Between Functional Status and Fatigue After COVID-19 Infection
Late Breaking Abstract - Implications of treatable traits and treatment choices on exacerbation risk in moderate-severe asthma
Risk factors of adverse outcome after acute hospitalization in Idiopathic Pulmonary Fibrosis (IPF)
Related content which might interest you:
Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning
Source: Virtual Congress 2021 – Acute COVID - 19
Year: 2021
Does Pre admission Quality Of Life Differ in Obese ICU patients?
Source: International Congress 2019 – Recent developments in intensive care unit medicine
Year: 2019
Late Breaking Abstract - Dynamic Early Warning Score versus National Early Warning Score-2 for predicting death or intensive care unit admission in respiratory patients
Source: Virtual Congress 2021 – E-health for COVID-19
Year: 2021
Birmingham Community Acquired Pneumonia Severity score (BCAPS) is a better predictor of mortality than CURB65 in hospitalised patients with community acquired pneumonia
Source: Virtual Congress 2020 – Clinical challenges in pneumonia
Year: 2020
Galectin-3 as predictor of mortality and ICU admission in patients with COVID 19 Acute Respiratory Failure
Source: Virtual Congress 2021 – Severe acute respiratory failure
Year: 2021
Predictors of 30-day mortality in elderly patients with community acquired pneumonia
Source: International Congress 2015 – CAP: prognostic factors in frail patients
Year: 2015
Quick Sepsis-related Organ Failure Assessment to predict ICU admission and mortality in community-acquired pneumonia
Source: International Congress 2017 – Hospital-acquired infections: from prevention to treatment
Year: 2017
Performance-Based Functional Assessment predicts length of hospital stay in pneumonia inpatients
Source: International Congress 2019 – Insights into assessment of functional status in respiratory disease patients
Year: 2019
Severe CAP: Can the CURB65 score and PT discriminate between ICU survivors and non-survivors?
Source: Annual Congress 2013 –Infection, sepsis and outcomes in ICU
Year: 2013
Impact on in-hospital mortality of Ceftaroline versus standard of care in Community-Acquired Pneumonia: A Propensity Matched Analysis
Source: Virtual Congress 2021 – Pneumonia
Year: 2021
Late Breaking Abstract - Variable costs of sepsis in a Greek ICU
Source: Virtual Congress 2021 – Difficult decisions on expected outcomes: availability of hospital resources and improvement of treatment adherence
Year: 2021
Prognostic power of biomarkers to predict in-hospital and postdischarge mortality in community acquired pneumonia
Source: Annual Congress 2013 –A modern approach to lung diseases: from bronchi to pleura
Year: 2013
Studying the association between mortality in patients requiring hospital admission for Community Acquired Pneumonia and pre-hospital antibiotic treatment in primary care
Source: International Congress 2017 – Discussion of vaccines, biomarkers and risk factors analysis
Year: 2017
Reducing length of stay for patients with Motor Neurone Disease admitted to a Specialist Ventilation Unit
Source: International Congress 2019 – Treatment of acute respiratory failure with noninvasive ventilation
Year: 2019
Home rehabilitation to improve respiratory muscles in patients recovering from a prolonged ICU stay and in-hospital rehabilitation
Source: International Congress 2014 – Best posters in pulmonary rehabilitation 2
Year: 2014
Validity of APACHE II and SOFA score in Predicting Prognosis in Mechanically Ventilated Patients in Respiratory ICU
Source: Virtual Congress 2021 – Acute non-invasive respiratory therapies in COVID-19 and beyond
Year: 2021
Mortality prediction in intermediate Respiratory Care Units:a novel use of Artificial Intelligence
Source: International Congress 2019 – Current trends in noninvasive ventilation for acute respiratory failure
Year: 2019
Assessing an Educational Intervention to Improve Recognition of Frailty in Hospitalized Patients with COPD
Source: International Congress 2019 – Medical education
Year: 2019
Does the Outpatient Pulmonary Rehabilitation Program Affect Mortality in Patients with COPD?
Source: Virtual Congress 2020 – Personalised treatment of obstructive diseases
Year: 2020
Risk of respiratory hospital admission in preterm children
Source: International Congress 2014 – Monitoring airway diseases with lung function tests
Year: 2014
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking "Accept", you consent to the use of the cookies.
Accept