View Proposal
-
Proposer
-
Heba Elshimy
-
Title
-
Smart Triage: AI-Assisted Emergency Severity Assessment Using Multimodal Patient Data
-
Goal
-
-
Description
- Patients visiting the emergency room / emergency department are assessed at triage by a single care provider and asked a series of questions to assess their current health status. Their vital signs are measured and a level of acuity is assigned. Based on the level of acuity, the patient either waits in the waiting room for later attention, or is prioritized for immediate care.
- Resources
-
Dataset (multimodal): https://mimic.mit.edu/docs/iv/modules/ed/triage (access will be provided when starting the project).
Suggested reading: A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system: https://www.nature.com/articles/s41598-024-80268-7
-
Background
-
Python, PyTorch/TensorFlow/Keras
-
Url
-
-
Difficulty Level
-
Moderate
-
Ethical Approval
-
None
-
Number Of Students
-
1
-
Supervisor
-
Heba Elshimy
-
Keywords
-
-
Degrees
-
Bachelor of Science in Computer Science
Master of Science in Artificial Intelligence
Master of Science in Data Science
Bachelor of Science in Computing Science