SACM - Malaysia
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9660
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Item Restricted HEART DISEASE CLASSIFICATION USING ARTIFICIAL INTELLIGENCE, CNN(Saudi Digital Library, 2023-08-09) Almakrami, Haidar; Sallehudin, HasimiThis thesis addresses the challenge of accurately classifying heart disease using a Heart Disease Classification model, which combines Convolutional Neural Networks (CNN) and BiLSTM. The study collects and preprocesses a comprehensive medical dataset related to heart disease. It then designs and trains CNN, RNN, and Combined models to capture complex patterns and temporal dependencies in the data. The results show that the Combined-2 (COMB-2) model outperforms others, achieving an accuracy of 0.964 and significant improvements in classification metrics. This research has implications for early diagnosis and improved healthcare in heart disease cases, showcasing the effectiveness of combining CNN and RNN models for classification.39 0