AI-driven pneumonia diagnosis from chest x-rays
Pneumonia remains a significant global health issue, especially in areas with limited diagnostic resources. Traditional methods for diagnosing pneumonia from chest X-rays are slow and require expert radiologists. We developed an AI-powered pneumonia detection tool using convolutional neural networks...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Faculty of Pharmacy
2025
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/121332/1/121332.pdf https://ir.uitm.edu.my/id/eprint/121332/ http://ijpncs.uitm.edu.my/index.php/en/ijpncs-journal |
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| Summary: | Pneumonia remains a significant global health issue, especially in areas with limited diagnostic resources. Traditional methods for diagnosing pneumonia from chest X-rays are slow and require expert radiologists. We developed an AI-powered pneumonia detection tool using convolutional neural networks (CNNs) with VGG16 and Inception models. These models were trained on chest X-ray datasets and achieved high accuracy in classifying pneumonia. Our app, built with Flask, allows healthcare professionals to uploadX-rays and get real-time predictions with confidence scores. The system supports continuous learning through user feedback, improving its performance. This tool can potentially revolutionise pneumonia diagnosis, especially in lowresource settings. |
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