搜索资源列表
pepp
- This code contains region growing segmentation algorithm to obtain the similar edges in color images
breast
- 简单的语言程序！比较简单，可很好的哦！以使用哦！-Simple language program! Relatively simple, you can use Oh!
A_stationary_DBT_system
- 静态数字乳腺层析成像系统设计论文，国外高质量论文-stationary digital breast tomosynthesis system
BBioinfYeastzr
- 乳腺癌分类程序，带有有部分的原始数据，非常好 -Breast cancer classification procedures, raw data, with some very good
GBayesian_Claa
- 使用高斯模型对威斯康辛州大学医学院长期乳腺癌数据进行了贝叶叶斯模式识别。识别率为95以上，可以作为模式识别的重要案例。 -Gaussian model the long-term breast cancer data of the University of Wisconsin School of Medicine the Bayeux Yates pattern recognition. Recognition rate of 95 or more can be used as the p
fengxiong
- 非常漂亮的丰胸单页网站源码,适合初学者做网站-Very nice breast single-page website source code
CODE1
- Histology images reveal grade-differentiating parameters for breast cancer
LVQ-neural--network-classification
- 本程序用于LVQ神经网络的分类——乳腺肿瘤诊断-This procedure for LVQ neural network classification- breast cancer diagnosis
LVQnn01
- LVQ神经网络的分类——乳腺肿瘤诊断,很有效果-LVQ neural network classification- breast cancer diagnosis
breast-classification
- obtain the complete source code for Breast Density Classification System
breast-tumor-diagnosis-based-on-BP
- LVQ神经网络的分类——乳腺肿瘤诊断相关程序-The classification of LVQ neural network- breast cancer diagnosis relative program
medical-new
- expert system for breast cancer diagnosis
breast_figure
- breast数据集的极限学习机的分类算法，自己编写的，可以运行-Extreme Learning Machine classification algorithm breast datasets, write your own, you can run
[3]pawar2016
- Genetic Fuzzy System (GFS) based Wavelet Co-occurrence Feature selection in Mammogram Classification for Breast Cancer Diagnosis
breast-cancer-wisconsin.data
- 分类数据集，一般用于机器学习，数据挖掘等(breast;cancer;wisconsin;data)
data
- breast cancer dataset
breast_cancer_classification
- Breast cancer detection using matlab
biomasscaulature
- 林木生物量方程和林分树高胸径方程及其参数初值(The equation of tree biomass and the high breast diameter equation of the forest tree and its initial parameters)
apriori-medical
- 借助乳腺癌患者的病理信息，挖掘患者症状与中医症状之间的关联关系；为治疗提供依据，挖掘潜在的病症因素。(With the help of pathological information of breast cancer patients, the relationship between patient symptoms and TCM symptoms can be excavated.)
classifier_D
- 使用SVM分类器来预测乳腺癌病人的预后(特征选择；分类器构建)，评价模型时使用无被交叉验证，性能评价指标包括准确率，AUC，灵敏度，特异度。学会最基本的机器学习方法。可查看分发给大家的代码，以后遇到类似的问题，可用相似的思路和代码。(The SVM classifier was used to predict the prognosis of breast cancer patients (feature selection; classifier construction), and the