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Deploying Machine Learning Models Using Progressive Web Applications: Implementation Using a Neural Network
Nuredin I Mohammed1, Alexander Jarde1, Grant Mackenzie1
1Medical Research Council Unit, The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, Gambia.
Frontiers in Public Health
|March 7, 2022
Summary
Progressive web applications (PWAs) enable offline deployment of artificial intelligence (AI) tools for healthcare, overcoming connectivity barriers. This facilitates AI/ML application use in resource-limited settings, improving patient triage and outcomes.
Area of Science:
- Medical Informatics
- Computer Science
Background:
- Deploying artificial intelligence (AI) and machine learning (ML) tools in healthcare faces challenges due to internet dependency and platform-specific requirements, especially in resource-limited settings.
- Traditional web and native mobile applications struggle with accessibility and maintenance in diverse environments.
Purpose of the Study:
- To explore the use of progressive web applications (PWAs) for deploying AI/ML tools in healthcare.
- To demonstrate the migration of a pneumonia mortality prediction tool to an offline-capable PWA for improved accessibility.
Main Methods:
- Utilized progressive web application (PWA) technology for cross-platform compatibility (desktop, iOS, Android).
- Developed an offline-first PWA for a neural network-based pneumonia mortality prediction triage tool.
- Enabled application installation as a native app on mobile devices without platform-specific coding.
Main Results:
- Successfully migrated a pneumonia mortality prediction tool from a prototype to an offline-capable mobile PWA.
- The PWA runs entirely offline after initial download, utilizing cached data and JavaScript execution.
- The application functions seamlessly on mobile devices, mimicking native app installation without app store complexities.
Conclusions:
- Machine learning applications can be deployed as platform-independent, offline progressive web applications (PWAs).
- PWAs are ideal for e-health applications in resource-limited settings, enhancing clinical decision-making and patient care.
- This approach supports UN Sustainable Development Goal 3 (SDG3) by improving health outcomes and saving lives.
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