NS-Assist: Nephrotic Syndrome Assistance System for Pediatric Decision-Making in Pandemic Situations
The COVID-19 pandemic has underscored the need for telemedicine to ensure continuity of pediatric care during health emergencies. This paper presents NS-Assist, a hybrid web–mobile decision support system for managing Idiopathic Nephrotic Syndrome (INS) in children. The system combines rule-based reasoning and fuzzy inference to assist clinicians in diagnosis, treatment adjustment, and relapse monitoring, while enabling caregivers to record and track daily health data. Implemented using Spring Boot, ReactJS, and Flutter with a secure MySQL database, NS-Assist integrates medical expertise with computational intelligence to support remote decision-making. A pilot evaluation involving 40 participants, including clinicians and caregivers, showed improved communication, reduced consultation time, and enhanced follow-up continuity. These results highlight the system’s potential as a reliable and adaptable framework for pediatric telemedicine in resource-constrained and emergency settings.
Authors
- Nardjes Bouchemal (ORCID: https://orcid.org/0000-0001-6105-2152)
- Galina Ivanova (ORCID: https://orcid.org/0000-0001-7799-1162)
- Imane Boussebough (ORCID: https://orcid.org/0000-0002-7544-6803)
- Nada Zendaoui (ORCID: https://orcid.org/0000-0001-6055-0854)
- Naila Bouchemal (ORCID: https://orcid.org/0000-0001-8294-9276)
Institutions
- Intelligent Systems Research (United States) (US)
- École Centrale d'Électronique (FR)
- Centre Universitaire de Mila (DZ)
- Université Constantine 2 (DZ)
- Angel Kanchev University of Ruse (BG)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-10-26
- DOI
- https://doi.org/10.3390/app152111433
- Citations
- 1
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 1.54
Funders
- European Commission