Abstract
Neural networks have become a transformative tool in health monitoring systems, ranging from wearable devices to complex predictive models. This article explores the applications of neural networks in health monitoring, highlighting their use in wearables for real-time data collection and their integration into predictive models for early disease detection and personalized healthcare. The article discusses the various neural network architectures employed, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and their impact on improving the accuracy and efficiency of health monitoring systems
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