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Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHRs in breast cancer risk prediction. We conducted a retrospective case-control study, gathering patients' ICD-9 diagnosis codes from an existing EHR data repository. Based on the hierarchical structure of ICD-9 codes, which are composed of 3-5...
Data mining (DM) is a collection of algorithms that are used to find some novel, useful and interesting knowledge in databases. DM algorithms are based on applied fields of mathematics and informatics, such as mathematical statistics, probability theory, information theory, neural networks. Some methods of these fields can be used to find hidden relation between data, what can be used to create models...
Breast cancer is one of the main causes of death among American women. The use of screening mammography is widely recommended for early diagnosis of breast cancer. In this paper, we propose a highly efficient algorithm for medical mammogram image classification, based on the generalized Beta mixture model. The proposed method, first extracts texture information from mammographic images then model...
In recent years, the breast cancer has become one the most common cancer among women. The challenge faced currently is how to implement the early detection and accurate diagnosis for this disease. In this paper, we first introduced the definition of Bayesian network and discussed its advantages in the fields of medicine diagnosis and prognosis. Then, the original breast cancer data records used for...
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