Abstract
Machine learning (ML) is transforming the healthcare industry by enabling the analysis and prediction of health trends based on vast datasets. This paper investigates the application of machine learning in healthcare, focusing on the prediction of diseases, patient outcomes, and large-scale health trends such as epidemics and pandemics. Machine learning algorithms can process both structured and unstructured data from various sources, including wearable devices and social media, offering significant benefits in disease detection, patient care, and resource allocation. However, challenges such as data bias, privacy concerns, and model interpretability remain barriers to the widespread adoption of ML in predicting health trends. The paper discusses recent advancements, case studies, and future opportunities in this rapidly evolving field, illustrating the potential of machine learning to revolutionize health prediction while highlighting areas requiring further research and ethical considerations. Keywords: Machine learning, Health trend prediction, Healthcare data, Disease detection, Epidemics, Artificial intelligence.
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