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首页> 外文期刊>Journal of Theoretical and Applied Information Technology >NAIVE BAYES CLASSIFIER AND FUZZY LOGIC SYSTEM FOR COMPUTER - AIDED DETECTION AND CLASSIFICATION OF MAMMAMOGRAPHIC ABNORMALITIES
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NAIVE BAYES CLASSIFIER AND FUZZY LOGIC SYSTEM FOR COMPUTER - AIDED DETECTION AND CLASSIFICATION OF MAMMAMOGRAPHIC ABNORMALITIES

机译：朴素贝叶斯分类器和模糊逻辑系统的乳房X线畸形计算机辅助检测和分类。

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Breast cancer has been one of the major causes of death among women since the last ten years and it has become an emergency for the healthcare systems of industrialized nations. This disease became the most common cancer among women. Today, detecting breast cancer at its early stage is the primary factor that will increase the chances of survival and will provide more options for treatment. Because of this, the proponent develops a computer ? aided detection and classification system for mammographic abnormalities. These abnormalities are limited only with microcalcification and masses. These abnormalities are classified as to benign or malignant.The system is divided into three modules: (1) detection of microcalcification, (2) classification of microcalcification and (3) classification of masses. The proponent used a Naive Bayes Classifier in detecting microcalcification and Fuzzy Logic System for classification of the severity of abnormalities. The data used were obtained from the Mammographic Image Analysis Society (MIAS) database.
机译：自最近十年以来，乳腺癌一直是妇女死亡的主要原因之一，它已成为工业化国家医疗系统的紧急情况。这种疾病成为女性中最常见的癌症。今天，在早期发现乳腺癌已成为增加生存机会并提供更多治疗选择的主要因素。因此，支持者开发了计算机？乳房X光检查异常的辅助检测和分类系统。这些异常仅受微钙化和肿块的限制。这些异常分为良性或恶性。系统分为三个模块：（1）微钙化的检测，（2）微钙化的分类和（3）质量分类。支持者使用朴素贝叶斯分类器检测微钙化，并使用模糊逻辑系统对异常严重程度进行分类。所使用的数据是从乳腺图像分析学会（MIAS）数据库获得的。

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