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.

7/6/2024 12:00:00 AM

83204

1403/04/28

DATA MINING IN ALZHEIMER'S DISEASE PREDICTION

داده كاوي، يادگيري ماشين، مراقبت هاي بهداشتي، آلزايمر، پيش بيني

data mining , machine learning , healthcare , Alzheimer's , prediction