Insight into breast cancer detection: new hybrid feature selection method
نویسندگان
چکیده
Abstract Breast cancer, which is also the leading cause of death among women, one most common forms disease that affects females all over world. The discovery breast cancer at an early stage extremely important because it allows selecting appropriate treatment protocol and thus, stops development cells. In this paper, a new patients detection strategy has been presented to identify with earlier. proposed composes two parts are data preprocessing phase patient (PDP). purpose study introduce feature selection methodology for determining efficient significant features identifying patients. This method known as hybrid (NHFSM). NHFSM made up modules quick module uses information gain, bat algorithm particle swarm optimization. Consequently, combines advantages optimization based on filter eliminate many drawbacks such being stuck in local optimal solution having unbalanced exploitation. preprocessed then used during PDP order enable accurate Based experimental results, improves efficiency patients’ classification comparison state-of-the-art approaches by roughly 0.97, 0.76, 0.75, 0.716 terms accuracy, precision, sensitivity/recall, F -measure. contrast, lowest error rate value 0.03.
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ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2022
ISSN: ['0941-0643', '1433-3058']
DOI: https://doi.org/10.1007/s00521-022-08062-y