Enhancing Hepatitis Patient Survival Detection: A Comparative Study of CNN and Traditional Machine Learning Algorithms - DIQI, MOHAMMAD; HISWATI, MARSELINA ENDAH; DAMAYANTI, EKA (Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau, 2024)
Hepatitis patient survival prediction is a critical medical task impacting timely interventions and healthcare resource allocation. This study addresses this issue by exploring the application of a Convolutional Neural Network (CNN) and comparing it with traditional machine learning algorithms, including Support Vector Machine (SVM), Decision Tree, k-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and Gradient Boosting (GBoost). The research objectives include evaluating the algorithms' performance regarding confusion matrix metrics and classification reports, aiming to achieve accurate predictions for both