BIG DATA ANALYTICS AND DATA MINING ARTIFICIAL INTELLIGENCE IN HEALTHCARE

Paper ID: EIJTEM_2022_9_1_20-26

Author's Name: MANOJ PAL

Volume: 9

Issue: 1

Year: 2022

Page No: 20-26

Abstract:

The healthcare industry is experiencing a paradigm shift driven by the exponential growth of data generated from electronic health records (EHRs), medical imaging, genomic sequencing, and wearable technologies. Traditional data processing methods are insufficient to harness the full potential of these vast datasets. This research investigates the transformative role of Big Data Analytics (BDA) and Data Mining (DM) techniques powered by Artificial Intelligence (AI) in improving healthcare outcomes. The study employs a mixed-methods approach, combining a review of recent AI applications with a performance evaluation of machine learning models applied to anonymized healthcare datasets. Techniques such as classification, clustering, and predictive modeling are analyzed using tools like Python, Apache Spark, and TensorFlow. Key findings demonstrate that AI-enhanced BDA can significantly improve disease prediction accuracy, enable early diagnosis, optimize treatment plans, and support clinical decision-making. Moreover, precision medicine initiatives benefit from pattern recognition in large patient cohorts, enabling personalized therapies. However, challenges such as data privacy, algorithmic bias, and system interoperability persist. This research highlights the critical need for ethical, scalable, and interpretable AI solutions in healthcare and suggests pathways for future research and policy development.

Keywords: Big Data, Artificial Intelligence, Data Mining, Healthcare Analytics, Predictive Modeling, Precision Medicine, Machine Learning, Clinical Decision Support

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