Data Mining Techniques in Healthcare: Discovering Hidden Patterns for Disease Prevention, Treatment Optimization, and Medical Research Advancement
Abstract
Data mining techniques have become essential tools in modern healthcare for extracting meaningful insights from large and complex datasets. This study evaluates the role of data mining in discovering hidden patterns that support disease prevention, treatment optimization, and medical research advancement. A convergent mixed-methods approach was employed, combining quantitative data from 185 healthcare professionals and data analysts with qualitative insights from case studies and expert interviews. The findings demonstrate that data mining significantly improves predictive accuracy, enhances clinical decision-making, and accelerates medical research. However, challenges such as data quality, privacy concerns, and algorithmic complexity remain critical barriers. The study provides strategic recommendations for optimizing the use of data mining techniques in healthcare systems.
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Copyright (c) 2025 Fazliddin Arziqulov, Sayfullayeva Dilbar Izzatillayevna, Maxsudov Valijon Gafurjonovich (Author)
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