Stroke Prediction by using Optimization Techniques and Algorithms based on ML.
Stroke is a major disease that leads to death worldwide. To improve patient outcomes, early detection and medication are essential. Since traditional methods for predicting strokes are not very efficient, machine learning (ML) assists us in improving the accuracy of stroke prediction. ML algorithms can be trained on large datasets of patients to identify patterns and use different optimization techniques to find the most important factors for stroke prediction. In this project, we explored the back-end mathematics of optimization techniques, different algorithms, and their implementation. Our goal is to identify suitable features and develop an ML model that can accurately predict stroke risk in patients. At the end, we performed a comparative analysis of different models.
Keywords: Machine Learning, Stroke prediction
Tools: Python
Department: Department of Mathematics
Project Team Members
| Name |
Email |
|
Javeria Ameen
|
Javeria2020@namal.edu.pk |
|
Ahmed Abbas
|
abbas2020@namal.edu.pk |
Project Poster
