sing Artificial Intelligence (AI) to Predict Health Changes in Patients with Lung Infection admitted to Intensive Care Unit (ICU)
Not Applicable
- Conditions
- Health Condition 1: J09-J18- Influenza and pneumonia
- Registration Number
- CTRI/2024/08/071791
- Lead Sponsor
- Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
Inclusion Criteria
All adult patients admitted to ED, HDU and/or ICU during the study period with clinical diagnosis of pneumonia at admission.
Exclusion Criteria
1.Pregnant women.
2.Patients with diagnosed hospital-acquired pneumonia at admission.
3.Patients with advanced directives for non-escalation of care/palliative care.
4.Patients are not willing to give informed consent.
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Build and validate a multimodality Artificial Intelligence (AI) tool to predict clinical status over the next 24-48 hours (classification problem) of patients with pneumonia admitted to Emergency Department (ED), High Dependency Unit (HDU) and/or Intensive Care Unit (ICU) settings.Timepoint: 24 to 48 hours
- Secondary Outcome Measures
Name Time Method Build and validate a deep learning (DL) based image classification model to diagnose pneumonia on chest X-ray images.Timepoint: 24 to 48 hours