Predicting Congestive Heart failure using predictive analytics in AI
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Abstract
This research paper explores the application of predictive analytics in artificial intelligence (AI) to forecast the onset of Congestive Heart Failure (CHF). Leveraging advanced machine learning algorithms and patient data, our study aims to develop a robust predictive model capable of early detection of CHF risk factors. Key components include the analysis of demographic information, medical history, and vital signs, contributing to a comprehensive understanding of individual patient trajectories. By employing predictive analytics, we seek to enhance the accuracy of CHF prognosis, enabling timely interventions and personalized healthcare strategies.
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