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Detection of Pneumonia Infection by Using Deep Learning on a Mobile Platform
Alhazmi Lamia1, Alassery Fawaz2
1Department of Management Information System, College of Business Administration, Taif University, P.O Box 11099, Taif 21944, Saudi Arabia.
Computational Intelligence and Neuroscience
|August 9, 2022
Summary
A new mobile app uses deep learning to detect pneumonia from chest X-rays, making diagnosis more accessible. This AI tool aims to improve pneumonia detection where expert access is limited.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Mobile Health
Background:
- Pneumonia diagnosis relies on clinical evaluation and imaging, often limited by expert availability.
- Accurate and accessible diagnostic tools are crucial for timely pneumonia treatment.
Purpose of the Study:
- To develop a mobile application prototype for pneumonia detection using deep learning.
- To create an accessible AI-powered tool for classifying pneumonia from medical images.
Main Methods:
- Utilized a dataset of over 5,000 chest X-ray images for training.
- Employed Create ML, a high-level tool with a graphical interface, for image classification model development.
- Developed a mobile application to deploy the trained neural network model.
Main Results:
- Successfully trained an image classification model using deep learning techniques.
- The model is integrated into a mobile application for widespread accessibility.
- The development process was simplified using Create ML, requiring no specialized knowledge.
Conclusions:
- A functional mobile app prototype for pneumonia detection has been developed.
- Deep learning and accessible tools like Create ML can democratize medical diagnostics.
- The application offers a potential solution for improving pneumonia diagnosis in resource-limited settings.
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