The role of artificial intelligence in predicting and preventing chronic diseases using big health data
Code: G-1260
Authors: Babak Masoudi * ℗, بهار مسعودی
Schedule: Not Scheduled!
Tag: Biomedical Signal Processing
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Abstract:
Abstract
Background and aims: Chronic diseases impose a significant burden on individuals and healthcare systems worldwide. Predicting and preventing these diseases can reduce morbidity, improve quality of life, and lower healthcare costs. This study aims to investigate the role of artificial intelligence (AI) in predicting and preventing chronic diseases using big health data: Method: This research employs a systematic review and meta-analysis (where possible) of studies published in PubMed, Scopus, Web of Science, IEEE Xplore, and ACM Digital Library from 2010 to 2024. Studies that examined the application of AI in predicting or preventing chronic diseases using big health data were included.. Results: : AI, particularly machine learning and deep learning algorithms, has shown promising results in predicting and preventing chronic diseases such as diabetes, cardiovascular disease, and cancer. These technologies can be used in early detection, risk prediction, patient monitoring, lifestyle recommendations, and clinical decision support. However, challenges such as data quality, model interpretability, ethical concerns, and integration with existing healthcare systems need to be addressed. Conclusion: AI has significant potential to improve the prediction and prevention of chronic diseases. With further development of algorithms, improved data quality, and addressing existing challenges, AI is expected to play an increasingly important role in promoting public health. Future research should focus on long-term effectiveness evaluation, development of interpretable models, and formulation of ethical guidelines.
Keywords
Artificial Intelligence, Machine Learning, Chronic Diseases
