Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images.

ABSTRACT:

Introduction

The purpose of this study is to use deep learning and machine learning to learn and classify patients with cutaneous melanoma with different prognoses and to explore the application value of deep learning in the prognosis of cutaneous melanoma patients.

Methods

In deep learning, VGG-19 is selected as the network architecture and learning model for learning and classification. In machine learning, deep features are extracted through the VGG-19 network architecture, and the support vector machine (SVM) model is selected for learning and classification. Compare and explore the application value of deep learning and machine learning in predicting the prognosis of patients with cutaneous melanoma.

Result

According to receiver operating characteristic (ROC) cur

SUBMITTER: Li A 

PROVIDER: S-EPMC9441353 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature