INFLUENCE OF DATA MINING TECHNIQUES IN HEALTHCARE RESEARCH

International Journal of Scientific Innovation & and Development(IJSID) Published by Leilani Katie Publication and PRESS

Abstract

Healthcare research has experienced significant transformation due to the rapid growth of digital technologies and the increasing availability of healthcare data. Large amounts of medical information are generated daily from hospitals, diagnostic centers, electronic health records, laboratory reports, medical imaging systems, and wearable devices. Extracting meaningful knowledge from these massive datasets has become a challenging task for healthcare professionals and researchers. Data mining techniques have emerged as an effective solution for discovering hidden patterns, relationships, and valuable information from healthcare datasets. The application of data mining methods in healthcare research assists in disease prediction, diagnosis, patient monitoring, treatment planning, and decision making. This paper investigates the influence of data mining techniques in healthcare research and examines various data mining approaches, applications, advantages, challenges, and future opportunities.

References

1. J. Han and M. Kamber, Data Mining: Concepts and Techniques. 2. I. Witten and E. Frank, Practical Machine Learning Tools and Techniques. 3. T. Mitchell, Machine Learning. 4. R. Pressman, Software Engineering: A Practitioner's Approach. 5. S. Kumar et al., "Healthcare Data Mining Techniques and Applications," IEEE Journal of Healthcare Informatics, 2024. 6. L. Brown et al., "Machine Learning Applications in Medical Diagnosis," IEEE Access, 2025.

Keywords

Data Mining, Healthcare Research, Disease Prediction, Machine Learning, Electronic Health Records, Healthcare Analytics