Alzheimer's Disease predict

In this project, I developed a predictive model for Alzheimer's disease using techniques from Machine Learning. I started by collecting and preprocessing medical data, including features such as age, cognitive test scores, and patient history, where I handled missing values and normalized the data. Then, I split the dataset into training and testing sets and trained multiple classification models such as Logistic Regression and Random Forest to identify patterns associated with the disease. After evaluating the models using metrics like accuracy and recall, I selected the best-performing model and optimized its performance. Finally, I built a simple system that takes new patient data as input and predicts the likelihood of developing Alzheimer’s, بهدف دعم الكشف المبكر ومساعدة الأطباء في اتخاذ قرارات أفضل.