Fog-Enabled Modular Deep Learning Platform for Textual Data Mining in Healthcare for Pathology Detection in Burkina Faso

Domaine:

healthcarenatural language processing

Type de record:

paper

Créateur:

ConSad

Éditeur:

IOS

Hôte:

In this paper, we propose an architecture for a deep-learning based medical diagnosis support platform in Burkina Faso. This model is built by merging the diagnosis and treatment guide with models derived from textual data recovered via optical character recognition (OCR) on handwritten prescriptions and data from electronic health records. Through simulation, we compared two architectures adapted to the Burkinabe context – a fog-based architecture and cloud-based architecture – and the validated one is the solution best suited to the organization of the country’s health system.

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