Expert System Analysis Using Forward Chaining Method for Climate Change Disease Diagnosis

DOI

10.2991/978-94-6463-774-8_15How to use a DOI?

Keywords

Diseases Due to Climate Change; Expert Systems; Diagnosis; Forward Chaining

Abstract

Advancing technology and information systems are increasingly utilized to create tools that facilitate access to critical information. To address challenges in disease management and early detection linked to climate change, expert systems offer a promising solution. This study develops an expert system to diagnose climate change-associated diseases through the Forward Chaining inference method. The research begins with a literature review to identify disease symptoms, risk factors, and clinical characteristics. Subsequently, clinical data and relevant medical information are gathered to construct the system’s knowledge base. The Forward Chaining approach processes user-inputted patient symptoms, cross-referencing them with stored data to generate diagnoses. Testing reveals the system achieves 92.3% accuracy and 95.83% sensitivity, demonstrating reliability in supporting healthcare professionals with early disease detection and diagnosis. This system is anticipated to aid in preventing and controlling disease spread, support healthcare decision-making, and provide preliminary treatment guidance for communities.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Edwina Rudyarti
AU  - Suanda Saputra
AU  - Niko Suwaryo
PY  - 2025
DA  - 2025/06/26
TI  - Expert System Analysis Using Forward Chaining Method for Climate Change Disease Diagnosis
BT  - Proceedings of the 2nd World Conference on Health and Social Sciences (WCHSS 2024)
PB  - Atlantis Press
SP  - 150
EP  - 163
SN  - 2468-5739
UR  - https://doi.org/10.2991/978-94-6463-774-8_15
DO  - 10.2991/978-94-6463-774-8_15
ID  - Rudyarti2025
ER  -