Supervised breast cancer prediction using integrated dimensionality reduction convolutional neural network.

ABSTRACT:

Objectives

Breast cancer is a major health problem with high mortality rates. Early detection of breast cancer will promote treatment. A technology that determines whether a tumor is benign desirable. This article introduces a new method in which deep learning is used to classify breast cancer.

Methods

A new computer-aided detection (CAD) system is presented to classify benign and malignant masses in breast tumor cell samples. In the CAD system, (1) for the pathological data of unbalanced tumors, the training results are biased towards the side with the larger number of samples. This paper uses a Conditional Deep Convolution Generative Adversarial Network (CDCGAN) method to generate small samples by orientation data set to solve the imbalance problem of collected data. (2) F

SUBMITTER: Xu H 

PROVIDER: S-EPMC10162536 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature