Developing an Explainable Artificial Intelligence System for the Mobile-Based Diagnosis of Febrile Diseases Using Random Forest, LIME, and GPT

Developing an Explainable Artificial Intelligence System for the Mobile-Based Diagnosis of Febrile Diseases Using Random Forest, LIME, and GPT

Objectives This study proposes a mobile-based explainable artificial intelligence (XAI) platform designed for diagnosing febrile illnesses. Methods We integrated the interpretability offered by local interpretable model-agnostic explanations (LIME) and the explainability provided by generative pre-t...

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Bibliographic Details
Main Authors: Kingsley F. Attai, Constance Amannah, Moses Ekpenyong, Daniel E. Asuquo, Oryina K. Akputu, Okure U. Obot, Peterben C. Ajuga, Jeremiah C. Obi, Omosivie Maduka, Christie Akwaowo, Faith-Michael Uzoka
Format: Article
Language:English
Published: The Korean Society of Medical Informatics 2025-04-01
Series:Healthcare Informatics Research
Subjects:
natural language processing
artificial intelligence
machine learning
telemedicine
mobile applications
Online Access:http://e-hir.org/upload/pdf/hir-2025-31-2-125.pdf
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