CLASSIFICATION BY A STACKING MODEL USING CNN FEATURES FOR MEDICAL IMAGE DIAGNOSIS

被引：0

作者：

Mutasher Rashed, Baidaa ^{[1
]}

Popescu, Nirvana ^{[2
]}

机构：

[1] Computer Science Dept., National University of Science and Technology POLITEHNICA of Bucharest, Romania

[2] Computer Science Dept., University POLITEHNICA of Bucharest, Romania

来源：

UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science | 2024年 / 86卷 / 01期

关键词：

Convolutional neural networks;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Medical imaging coupled with Artificial Intelligence (AI) applications, in particular Deep learning (DL) and Machine Learning (ML), can speed up the disease diagnostic process. The purpose of this work is to present a novel disease detection system by suggesting a new Convolutional Neural Network (CNN) model and combining the CNN features with three of ML classifiers and suggesting a new classifier using the stacking model. The proposed system was used in binary and multi-classification and applied to two different medical datasets. The proposed model was evaluated using accuracy, sensitivity, specificity, precision, recall, F1 score, and AUC, achieving robust results. © 2024, Politechnica University of Bucharest. All rights reserved.

引用

页码：3 / 18