“Electronic Pediatrician”, a non-machine learning prototype artificial intelligence software for pediatric computer-assisted pathophysiologic diagnosis ― general presentation

EPed is the first and only physiopathology-based nml-AI KBS focused on general pediatrics and is the first and only pediatric Romanian 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.

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Publication Details

Journal
World Journal of Methodology
Published
2025-03-06
DOI
https://doi.org/10.5662/wjm.v15.i3.100903
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
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article

“Electronic Pediatrician”, a non-machine learning prototype artificial intelligence software for pediatric computer-assisted pathophysiologic diagnosis ― general presentation

Andrei-Lucian Drăgoi, Roxana-Maria Nemeș
World Journal of Methodology
Machine Learning in Healthcare
article

“Electronic Pediatrician”, a non-machine learning prototype artificial intelligence software for pediatric computer-assisted pathophysiologic diagnosis ― general presentation

Andrei-Lucian Drăgoi, Roxana-Maria Nemeș
article en

Abstract

EPed is the first and only physiopathology-based nml-AI KBS focused on general pediatrics and is the first and only pediatric Romanian 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.

World Journal of MethodologyVol. 15(3)
Titu Maiorescu University (RO), Valahia University of Targoviste (RO)
Openalex Percentile: Top 98%
Machine Learning in Healthcare
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