Titlebook: Intelligent Systems Modeling and Simulation III; Artificial Intellige Samsul Ariffin Abdul Karim Book 2024 The Editor(s) (if applicable) an

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Machine Learning Based Smart Health Monitoring System for COVID-19,e is designed to collect data on the most recent COVID-19 symptoms, utilizing machine learning for predictive analysis. Multiple functionalities, including data logging, IoT connectivity with data visualization, and an Email notification system, enhance its utility. Importantly, this prototype remai

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Intelligent LASSO Regression Modelling for Seaweed Drying Analysis,e performance of these three models was evaluated and compared using the following metrics: RMSE, MAE, MSE, MAPE, R-squared and adjusted R-squared. The result of the study revealed that LASSO regression fits this seaweed drying dataset better and has predictive performance at predicting the seaweed

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A Comparative Analysis of Machine Learning-Based Prediction for Heart Disease Detection, attributes, including Blood Pressure (BP), cholesterol (Chol), electrocardiogram (ECG), and a total number of 1026 data records. The chapter shows that the machine learning model LR achieves accuracy, precision, recall, and F1-score of 85%, 87%, 85%, and 86%, respectively; SVM achieves 85%, 87%, 85

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Understanding COVID-19 Recovery Dynamics in the MENA Region: A Geospatial Analysis of Key DeterminaGeographically Weighted Regression (MGWR) model results, indicating their central role in shaping COVID-19 recovery case outcomes in spatial regression models. As the first research exploration in the MENA region, this study and provides valuable insights for future research and public health interv

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