利用深度学习检测肺炎

IF 0.3

International Journal of Next-Generation Computing Pub Date : 2023-02-15 DOI:10.47164/ijngc.v14i1.1023

Nishant Borkar, Atharva Zararia, Riddhi Gangbhoj, Prashant Kumar, Vaishnavi Bhaiyya

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引用次数: 0

摘要

该研究论文的主要思想是通过病人的胸部x光来检测肺炎。肺炎是一种引起单肺或双肺气囊发炎的感染。气囊充满脓性物质(脓液)，导致呼吸急促、咳嗽、发烧、发冷。多种细菌、病毒和真菌可引起肺炎。在本文中，我们使用机器学习算法来处理x射线图像以确定患者是否患有肺炎。本实验主要利用VGG16预处理、keras和adams等深度学习算法来构建高精度的模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Detection of Pneumonia Using Deep Learning

The main idea of the research paper is to detect pneumonia from the patient’s chest x- rays. Pneumonia is the infection that causes inflammation of the air sacs in one or both the lungs. The air sacs are filled with purulent material (pus) causing breath shortness, cough, fever, chills.A variety of bacteria, viruses, and fungi can cause pneumonia. In this paper, we used machine learning algorithms to process x-ray images to determine whether or not the patient has pneumonia. This Experiment focusses on the use of deep learning algorithms with VGG16 pre-processing, keras and adams in order to build a model with high accuracy.

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来源期刊

International Journal of Next-Generation Computing COMPUTER SCIENCE, THEORY & METHODS-

自引率

66.70%

发文量