A rule-based recommender system for generating and explaining medical check-up reports

Martina Cahya Pratiwi; Retno Aulia Vinarti; Endah Indriastuti; Riris Diana Rachmayanti; Arif Djunaidy

doi:10.1016/j.procs.2026.07.086

A rule-based recommender system for generating and explaining medical check-up reports

Martina Cahya Pratiwi
, Retno Aulia Vinarti^*
, Endah Indriastuti
, Riris Diana Rachmayanti
, Arif Djunaidy

^*Corresponding author for this work

Department of Information Systems
Institut Teknologi Sepuluh Nopember
Department of Epidemiology
Universitas Airlangga
Medical Study Program

Research output: Contribution to journal › Conference article › peer-review

Abstract

Medical check-ups are comprehensive health assessments for individuals. This research develops a hybrid rule-based recommendation system implemented in a web-based application to generate personalized medical check-up reports. The development starts with knowledge acquisition through interviews with a clinical pathologist, followed by creating a knowledge base with 524 IF-THEN rules and 49 XAI, which is then implemented using forward chaining in a web-based application. The evaluation includes expert reviews, decision table testing (96.67% success rate), and qualitative usability testing, which shows user satisfaction. This research is expected to decrease health workers' workloads and increase understanding of patients' health status.

Original language	English
Pages (from-to)	992-999
Number of pages	8
Journal	Procedia Computer Science
Volume	284
DOIs	https://doi.org/10.1016/j.procs.2026.07.086
Publication status	Published - 2026
Event	8th Information Systems International Conference, ISICO 2025 - Hybrid, Bali, Indonesia Duration: 4 Aug 2025 → 6 Aug 2025

Keywords

Expert Systems
Medical Check-up Reports
Personalization
Recommendation Systems
Rule-base

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10.1016/j.procs.2026.07.086

Cite this

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title = "A rule-based recommender system for generating and explaining medical check-up reports",

abstract = "Medical check-ups are comprehensive health assessments for individuals. This research develops a hybrid rule-based recommendation system implemented in a web-based application to generate personalized medical check-up reports. The development starts with knowledge acquisition through interviews with a clinical pathologist, followed by creating a knowledge base with 524 IF-THEN rules and 49 XAI, which is then implemented using forward chaining in a web-based application. The evaluation includes expert reviews, decision table testing (96.67\% success rate), and qualitative usability testing, which shows user satisfaction. This research is expected to decrease health workers' workloads and increase understanding of patients' health status.",

keywords = "Expert Systems, Medical Check-up Reports, Personalization, Recommendation Systems, Rule-base",

author = "Pratiwi, \{Martina Cahya\} and Vinarti, \{Retno Aulia\} and Endah Indriastuti and Rachmayanti, \{Riris Diana\} and Arif Djunaidy",

note = "Publisher Copyright: {\textcopyright} 2026 The Author(s).; 8th Information Systems International Conference, ISICO 2025 ; Conference date: 04-08-2025 Through 06-08-2025",

year = "2026",

doi = "10.1016/j.procs.2026.07.086",

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AU - Pratiwi, Martina Cahya

AU - Vinarti, Retno Aulia

AU - Indriastuti, Endah

AU - Rachmayanti, Riris Diana

AU - Djunaidy, Arif

PY - 2026

Y1 - 2026

N2 - Medical check-ups are comprehensive health assessments for individuals. This research develops a hybrid rule-based recommendation system implemented in a web-based application to generate personalized medical check-up reports. The development starts with knowledge acquisition through interviews with a clinical pathologist, followed by creating a knowledge base with 524 IF-THEN rules and 49 XAI, which is then implemented using forward chaining in a web-based application. The evaluation includes expert reviews, decision table testing (96.67% success rate), and qualitative usability testing, which shows user satisfaction. This research is expected to decrease health workers' workloads and increase understanding of patients' health status.

AB - Medical check-ups are comprehensive health assessments for individuals. This research develops a hybrid rule-based recommendation system implemented in a web-based application to generate personalized medical check-up reports. The development starts with knowledge acquisition through interviews with a clinical pathologist, followed by creating a knowledge base with 524 IF-THEN rules and 49 XAI, which is then implemented using forward chaining in a web-based application. The evaluation includes expert reviews, decision table testing (96.67% success rate), and qualitative usability testing, which shows user satisfaction. This research is expected to decrease health workers' workloads and increase understanding of patients' health status.

KW - Expert Systems

KW - Medical Check-up Reports

KW - Personalization

KW - Recommendation Systems

KW - Rule-base

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DO - 10.1016/j.procs.2026.07.086

M3 - Conference article

AN - SCOPUS:105045834644

SN - 1877-0509

VL - 284

SP - 992

EP - 999

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 8th Information Systems International Conference, ISICO 2025

Y2 - 4 August 2025 through 6 August 2025

ER -

A rule-based recommender system for generating and explaining medical check-up reports

Abstract

Keywords

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