Project 460160
Machine learning for healthcare research
460160
Machine learning for healthcare research
$198,900
Project Information
| Study Type: | Unclear |
| Research Theme: | Clinical |
Institution & Funding
| Principal Investigator(s): | Austin, Peter C |
| Co-Investigator(s): | Lee, Douglas S; WANG, BO |
| Institution: | Sunnybrook Research Institute (Toronto, Ontario) |
| CIHR Institute: | Health Services and Policy Research |
| Program: | |
| Peer Review Committee: | Health Services Evaluation & Interventions Research 3 |
| Competition Year: | 2022 |
| Term: | 3 yrs 0 mth |
Abstract Summary
Predicting the probability of outcomes for patients is important for medical decision making. For example, know which patients are at higher risk of death can inform which patients should be treated more aggressively. Machine learning methods are methods from the field of Computer Science that can be used for predicting patient outcomes. There is growing interest in using machine learning methods to predict patient outcomes. The objective of this research is to improve the use of machine learning methods for predicting patient outcomes.
No special research characteristics identified
This project does not include any of the advanced research characteristics tracked in our database.
Keywords
Big Data
Machine Learning
Prediction Models
Risk Prediction