Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Methodol. Sep 20, 2025; 15(3): 100903
Published online Sep 20, 2025. doi: 10.5662/wjm.v15.i3.100903
“Electronic Pediatrician”, a non-machine learning prototype artificial intelligence software for pediatric computer-assisted pathophysiologic diagnosis ― general presentation
Andrei-Lucian Drăgoi, Roxana-Maria Nemeș
Andrei-Lucian Drăgoi, Roxana-Maria Nemeș, Medical Doctoral School of University "Titu Maiorescu", Bucharest 040051, Romania
Andrei-Lucian Drăgoi, The Emergency County Hospital Târgoviște (SJUT), Dambovita 130095, Târgoviște, Romania
Author contributions: Drăgoi AL designed, analyzed, interpreted, and prepared this paper; Nemeș RM has initially reviewed this paper and suggested important improvements in its form.
Institutional review board statement: It is not the case for this paper.
Informed consent statement: Patients were not additionally required to give informed consent to this study of the EPed software, because the analysis accomplished by EPed used anonymous data that were obtained after each parent of each admitted child-patient (diagnosed and treated in the Pediatric Infectious Diseases Ward of our hospital) agreed to all labs, imagistic and treatment interventions on his/her child by written consent (which consent was part of each medical folder in part).
Conflict-of-interest statement: The authors of this paper declare no existing competing interests.
Data sharing statement: No additional data.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Andrei-Lucian Drăgoi, MD, Doctor, Researcher, Medical Doctoral School of University "Titu Maiorescu", Str. General I. E. Florescu nr. 9, Bl. D11, Sc. B, Ap. 9, Bucharest 040051, Romania. dr.dragoi@yahoo.com
Received: September 6, 2024
Revised: October 24, 2024
Accepted: November 25, 2024
Published online: September 20, 2025
Processing time: 181 Days and 14.4 Hours
Core Tip

Core Tip: Electronic Pediatrician (EPed) is the first and only physiopathology-based non-machine learning artificial intelligence (nml-AI) knowledge-based system (KBS) focused on general pediatrics and is the first and only Romanian pediatric KBS addressed to medical professionals. Furthermore, EPed is the first and only nml-AI KBS that offers not only both a physiopathology-based differential and positive disease diagnosis, but also identifies possible physiopathological “clusters” that may explain the signs and symptoms of any child-patient and may help treating that patient physiopathologically (until a final diagnosis is found), thus encouraging and developing the physiopathological reasoning of any clinician.