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The Application of Data Mining in Medical Data Analysis

Author: ZuoYing
Tutor: MaoXiaoGuang
School: National University of Defense Science and Technology
Course: Computer technology
Keywords: Data Mining Medical Data Analysis Decision Tree Neural Networks Clustering Associate
CLC: TP311.13
Type: Master's thesis
Year: 2007
Downloads: 408
Quote: 7
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Abstract


With the depth formatted electronic medical records and medical information systems applications, the medical industry has accumulated a large amount of clinical data and management information. Traditional analysis methods are difficult from these complex, incomplete, non-standardized medical data found intrinsically linked reveal mode, laws. Data mining technology as a new data analysis method gradually applied to the analysis of medical data, extract law, predict trends, found a surprising pattern, which is very important to improve the effect of clinical diagnosis, to improve hospital decision-making level. Analysis method based on data mining has become a new way to improve the quality of medical services and hospital competitiveness. Depth development of health care reform, resulting in the health care market is increasingly competitive. The hospital overall development strategy formulation and adjustment of marketing strategy, a direct impact on its position in the medical market and competitiveness. Therefore, the requirements of the scientific decision-making is increasingly urgent. On the other hand, the Armed Police Hospital launched a comprehensive military health system for several years, has accumulated a large amount of clinical data and management information, laid a data base for scientific decision-making. In this paper, based on the raw data of the armed police of a Corps Hospital by demand for research to determine the distinction between high-yield disease development characteristics of diseases selected for the hospital to provide a basis for decision making; distinguish between high-hosting areas, provide for the medical market strategy formulation basis for decision making; research focus on disease and to provide basis for decision making, in order to regulate the treatment analysis tasks and objectives, highlighting the practical value of the results of the analysis. At the same time, using the classification method diabetes follow-up data. Study by clustering method to distinguish high-yield disease, a reasonable allocation of medical resources, the the hospitals selected characteristics specialist adjust development strategy to provide a basis for decision making; clustering method to distinguish patients with major source areas for the development of medical market strategy provide a reference; association analysis found that the complications of diabetes, and to provide a reference for the early prevention of type 2 diabetes complications; association analysis reveals uremia treatment medication, to find out the the medication law and deviation, specification uremia treatment and medicines audit to provide a basis; established type 2 diabetes prediction model using the C5.0 algorithms and BP neural network algorithm, secondary diagnosis reference for the clinical diagnosis of type 2 diabetes. Portions of this article analysis become an important basis for the hospital to formulate development strategies and adjust marketing strategies. In this paper, the raw data were analyzed to explore the extraction of data from the military health system, the data processing, data preprocessing, exploratory analysis, algorithm selection model and full analysis of the assessment process, the engineering analysis of medical data embodiment method provides a good reference. Provide a better idea for the analysis of complex medical information. This article is intended application, combined with demand determine the analytical tasks and goals, and highlight the results of practical value.

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