乳腺癌
人工智能
特征提取
模式识别(心理学)
计算机科学
鉴定(生物学)
过程(计算)
灵敏度(控制系统)
癌症
机器学习
医学
工程类
内科学
操作系统
生物
植物
电子工程
作者
Liang Zhang,Amita Nandal,Todor Ganchev,Amita Nandal
出处
期刊:International Journal of Intelligent Systems Technologies and Applications
[Inderscience Enterprises Ltd.]
日期:2022-01-01
卷期号:20 (6): 510-510
标识
DOI:10.1504/ijista.2022.128527
摘要
Breast cancer growth has become a typical factor nowadays. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerised features extraction and classification algorithms. In the recent times, breast cancer can be diagnosed by classifying tumours. In this paper, breast cancer identification and analysis is done by using machine learning statistical analysis. The proposed technique has proven to improve the exactness of foreseeing predicting cancer. The proposed method used optimised recording condition of the input image and later introduces a new interpretable feature for the identification. The simulation results are compared with conventional methods by using accuracy, sensitivity and specificity for performance assessment of the identification process.
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