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Using Artificial Intelligence (AI) to Predict Health Changes in Patients with Lung Infection admitted to Intensive Care Unit (ICU)

Development and validation of multimodality Artificial Intelligence (AI) tool for prediction of short-term changes in clinical status among patients with pneumonia requiring intensive care - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2024/08/071791
Enrollment
3000
Registered
2024-08-01
Start date
Unknown
Completion date
Unknown
Last updated
2024-08-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: J09-J18- Influenza and pneumonia

Interventions

Intervention1: NIL: NIL

Sponsors

Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal
Lead Sponsor

Eligibility

Inclusion criteria

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

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.

Design outcomes

Primary

MeasureTime frame
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

MeasureTime frame
Build and validate a deep learning (DL) based image classification model to diagnose pneumonia on chest X-ray images.Timepoint: 24 to 48 hours—

Countries

India

Contacts

Public ContactGanesh Paramasivam

Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal

ganesh.p@manipal.edu9914204224

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026