An IoT-based deep learning frame work for early assessment of pneumonia.
An IoT-based deep learning frame work for early assessment of pneumonia.
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Date
2024
Auteurs
MADANI Rihab
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Résumé
The COVID-19 pandemic has highlighted the importance of remote patient monitoring for the well-being of both patients and healthcare providers. Pneumonia, a leading cause of morbidity and mortality in children, requires prompt diagnosis and treatment due to its impact on the small air sacs in the lungs. Chest X-rays are a common diagnostic tool for detecting pneumonia. This study emphasizes the development of a support tool to assist healthcare professionals in enhancing the accuracy and efficiency of pneumonia diagnosis through advanced deep learning approaches. The best model accuracy of VGGNet of 95.89% confirms that the model is robust however MobileNet can perform well in real-world situations.
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Pneumonia, Internet of Medical Things (IoMT), Artificial intelligence, Deep learning, Edge computing, Cloud computing.