Abstract
This study demonstrates how artificial intelligence (AI) is transforming medical diagnosis, particularly for respiratory disorders such as COVID-19 and influenza. The project aims to enhance global healthcare systems by accurately and rapidly identifying respiratory disorders through AI-driven chest X-ray analysis. Given the significant public health implications of infections like COVID-19, the importance of this work is paramount. Convolutional Neural Networks (CNNs) are employed to analyze chest X-ray images and detect patterns indicative of viral infections. Key components of the project include convolutional blocks, the RMSprop optimizer, 2D max pooling, dropout regularization, and the categorical cross-entropy loss function. Two CNN models are developed from scratch to balance complexity and efficacy in X-ray image classification.
| Original language | English |
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| Title of host publication | 2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 71-75 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350384598 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024 - Hybrid, Gwalior, India Duration: 27 Jun 2024 → 28 Jun 2024 |
Publication series
| Name | 2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024 |
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Conference
| Conference | 3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024 |
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| Country/Territory | India |
| City | Hybrid, Gwalior |
| Period | 27/06/24 → 28/06/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Artificial Intelligence
- Chest X-ray Analysis
- Convolutional Neural Networks
- COVID-19 Diagnosis
- Respiratory Disorders
