Stroke Risk Prediction with Machine Learning Techniques
importance 8/10
ai assisted
Artificial Intelligence in Healthcare stroke medicine stage: research
Problem
Predicting long-term risk of stroke occurrence early enough to enable prevention and healthier living.
Why it matters
Stroke causes death and long-term disability; early prediction can save lives.
What the AI did
Developed and evaluated several machine learning models; a stacking ensemble classifier achieved the best long-term stroke risk prediction.
Results
AUC 98.9%, F-measure/precision/recall 97.4%, accuracy 98%.
Impact
Stacking outperformed other tested methods on the study dataset.
Record
| Venue | Sensors |
|---|---|
| Published | 2022 |
| Work type | article |
| Authors | Elias Dritsas, Μαρία Τρίγκα |
| Citations | 284 (OpenAlex, at import time) |
| References | 68 |
| Model or method | Stacking classification ensemble |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/s22134670 |
| Open access | gold |
| Keywords | stroke prediction, machine learning, stacking ensemble, AUC, healthcare |
Importance rating
8
major — millions of lives, an industry or a field
Stroke causes death and disability depending on brain region affected; early prediction could save lives and promote healthy living. Abstract gives no scale figures.