| Abstrakt: |
A recent study conducted at Koneru Lakshmaiah Education Foundation in Andhra Pradesh, India, focused on stroke prediction using machine learning techniques. The researchers proposed a model that utilizes polynomial feature transformation and linear regression to capture both linear and non-linear relationships in brain stroke data. The model demonstrated superior performance with a testing accuracy of 99.2%, highlighting the potential of linear regression with polynomial features for accurate predictions and insights into feature-target relationships. This research contributes to the field of stroke prediction by offering a balanced approach that considers model complexity and interpretability. [Extracted from the article] |
