Web Diagnosis for COVID-19 and Pneumonia Based on Computed Tomography Scans and X-rays

被引：2

作者：

Antunes, Carlos ^{[1
]}

Rodrigues, Joao M. F. ^{[2
,3
]}

Cunha, Antonio ^{[1
,4
]}

机构：

[1] Univ Tras Os Montes & Alto Douro, Vila Real, Portugal

[2] Univ Algarve, NOVA LINCS, Faro, Portugal

[3] Univ Algarve, ISE, Faro, Portugal

[4] Inst Syst & Comp Engn, Technol, Porto, Portugal

来源：

UNIVERSAL ACCESS IN HUMAN-COMPUTER INTERACTION, PT III, UAHCI 2024 | 2024年 / 14698卷

关键词：

Web Diagnosis Application; COVID-19; Pneumonia; CONVOLUTIONAL NEURAL-NETWORK; ENSEMBLE;

D O I：

10.1007/978-3-031-60884-1_14

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Pneumonia and COVID-19 are respiratory illnesses, the last caused by the severe acute respiratory syndrome virus, coronavirus 2 (SARS-CoV-2). Traditional detection processes can be slow, prone to errors, and laborious, leading to potential human mistakes and a limited ability to keep up with the speed of pathogen development. A web diagnosis application to aid the physician in the diagnosis process is presented, based on a modified deep neural network (AlexNet) to detect COVID-19 on X-rays and computed tomography (CT) scans as well as to detect pneumonia on X-rays. The system reached accuracy results well above 90% in seven well-known and documented datasets regarding the detection of COVID-19 and Pneumonia on X-rays and COVID-19 in CT scans.

引用

页码：203 / 221

页数：19

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