Healthcare
❯
Real-Time Patient Triage
❯Hospital Patient Management
❯Machine-learning based triage to determine low-severity patients that can be fast-tracked to admission in ED due to their short discharge length
Hospital management tools
For:
Hospital administrator
Scope:
Temporal data mining, visualization
Goal:
Improve Operation Efficiency
Generation of clinical pathways
For:
Nursing staff
Scope:
Decision tree, clustering
Goal:
Improve Operation Efficiency
Machine-learning based triage to determine low-severity patients that can be fast-tracked to admission in ED due to their short discharge length
For:
Emergency Departments in hospitals.
Goal:
Improved Employee Efficiency
Discharge summary classifier
For:
Medical staff
Scope:
Decision tree, random forest, SVM, BNN, deep learning
Goal:
Improve Operation Efficiency
Real-time patient support and medical information service applying spoken dialogue system
For:
Dentist
Hospital
Scope:
Medical business support system using artificial intelligence-based human-
computer interface technology.
Goal:
Other
Machine-learning based triage to determine low-severity patients that can be fast-tracked to admission in ED due to their short discharge length
For:
Emergency Departments in hospitals.
Goal:
Improved Employee EfficiencyProblem addressed
Overcrowding in emergency departments (ED) is a critical problem worldwide, and streaming can alleviate crowding to improve patient flows. Among triage scales, patients labeled as “triage level 3” or “urgent” generally comprise the majority, but there is no uniform criterion for classifying low-severity patients in this diverse population.
The goal was to establish a machine learning model for prediction of low-severity patients with short discharge length of stay. These patients could then be fast-tracked into admission and release.
Description
Both internal and external validation had to be performed in order to build and test the model. A Jan. 2018 to Dec. 2018 dataset from China Medical University Hospital (CMUH) was used for model construction and internal validation, and another from Jan. 2018 to Dec. 2019 from Asia University Hospital (AUH) was applied for external validation.
Raw Data
AI: Perceive
Machine Learning
AI: Understand
Predict / Forecast
AI: Act