BIG DATA AND MACHINE LEARNING IN HOSPIT ALS: significant advances in hospital management
avanços significativos na gestão hospitalar
DOI:
https://doi.org/10.31510/infa.v22i2.2338Keywords:
Healthcare, Big Data, Electronic Medical Records, Machine LearningAbstract
In recent years, Big Data has become increasingly dominant in healthcare, driven by three main factors: the sheer volume of available data, rising healthcare costs, and the demand for personalized care. Big Data processing in healthcare refers to the generation, collection, analysis, and storage of clinical data too vast or complex to be processed by traditional data processing methods. Sources of Big Data for healthcare include the Internet of Things (IoT), Electronic Health Records (EHRs), which contain patient medical history, diagnoses, medications, treatment plans, allergies, laboratory and test results, genomic sequencing, medical images, health insurance plans, and other clinical data. This study's methodology follows a structured approach to review the impact of Big Data and Machine Learning (ML) on healthcare information management.
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