چکيده
The goal of this research is to use machine learning algorithms to create precise
Alzheimer ‘s disease prediction models for prognosis, diagnosis, and early
detection. We investigate the broad applicability of machine learning techniques
across multiple medical domains through a thorough assessment of the literature,
emphasizing their effectiveness in Alzheimer's prediction. Data collection,
preprocessing, feature selection, model training, assessment, and comparison are
all part of our methodology. We aimed to build prediction models for prediction
using logistic regression, random forest, and support vector machines. We then
would evaluate the models' performance on pertinent datasets using important
metrics like accuracy, precision, recall, and F1-score.
