Big Data in the Revolution of Medical Data: A Review

Abstract

Big Data plays a crucial role in the medical sector, fundamentally transforming the collection, organization, and interpretation of medical data. This shift significantly enhances healthcare quality, propels medical research, and improves healthcare system effectiveness. Medical Big Data comprises a vast and diverse array of health-related information, generated at an unprecedented scale and speed, including electronic health records, medical imaging, genomic data, clinical trials, and data from wearable devices. Analyzing this data can reveal vital insights into disease patterns, treatment effectiveness, and population health trends, thereby aiding in the creation of personalized medicine, predictive analysis, and innovative healthcare solutions. Effective utilization of Medical Big Data requires advanced computational and analytical methods to extract meaningful insights, thereby fueling progress in healthcare and medical research. This review aims to provide specialists with a comprehensive overview of Big Data's application in diagnostic and medical domains, including its current usage in healthcare. We particularly focus on how the integration of Big Data with artificial intelligence has led to more accurate predictive models for disease outbreaks and patient health risks, enhancing preventive care strategies. Furthermore, our analysis indicates that Big Data-driven personalization of treatment has significantly improved adherence to therapies and health outcomes in chronic disease management.