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Causal Inference for Personalized Geriatric Well Being: A Bayesian Network Approach
Abstract
In today's digital world, recommendation systems are like smart tools that make our online experiences better. Personalized recommendation systems have become a powerful tool for people who would rather improve and control their own health in the ever-changing healthcare environment of today. Even in situations when an individual is on their own, these systems leverage the power of digital technology and data analysis to provide personalized guidance and support for a range of healthcare tasks. Personalized recommendation systems provide customized solutions that consider the unique requirements and preferences of single people, whether the issue is managing mental health concerns, adhering to a balanced diet, managing chronic illnesses, or sustaining physical activity. By using these systems to their full potential, people may take charge of their health and well-being, making educated decisions and achieving their healthcare goals with more confidence and efficiency.
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