Xiao Lingxian
College of Medicine, Jingchu University of Technology, Jingmen 448000, China
Xu Qianqian
College of Medicine, Jingchu University of Technology, Jingmen 448000, China

DOI:https://doi.org/10.5912/jcb2485


Abstract:

As an interdisciplinary field combining biotechnology, medical science, and data mining, the application of advanced data analysis techniques has become a critical direction for medical research worldwide. The cardiothoracic ratio (CTR), an important indicator of heart and thoracic health, has been increasingly studied in relation to aging, providing valuable insights into age-related physiological changes. The improvement and application of data mining (DM) technology offer innovative solutions to challenges that traditional diagnostic methods cannot address. DM is particularly effective in extracting meaningful information and patterns from large volumes of medical data, enabling scientific decision-making in disease diagnosis and treatment. This paper focuses on the analysis of the relationship between cardiothoracic ratio and aging using DM algorithms. By leveraging data mining and computer technologies to process and analyze medical images, this study extracts valuable features and patterns embedded in the data. The results of this approach have significant implications for biotechnology-driven commercial foresight, supporting business decision-making, scientific research, and medical advancements. The proposed method demonstrates a 14.26% improvement in accuracy compared to traditional manual methods, highlighting its suitability for widespread application. It reveals rich feature information and rules, providing actionable insights that assist in clinical diagnosis and enable predictive modeling for age-related changes in cardiothoracic health. This research underscores the academic value and practical potential of DM in advancing biotechnology and medical science, offering robust tools for both commercial applications and clinical practice.