{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T01:10:33Z","timestamp":1741223433863,"version":"3.38.0"},"reference-count":15,"publisher":"Baishideng Publishing Group Inc.","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["World J Methodol"],"abstract":"<jats:p>BACKGROUND<\/jats:p>\n          <jats:p>Knowledge-based systems (KBS) are software applications based on a knowledge database and an inference engine. Various experimental KBS for computer-assisted medical diagnosis and treatment were started to be used since 70s (VisualDx, GIDEON, DXPlain, CADUCEUS, Internist-I, Mycin etc. ).<\/jats:p>\n          <jats:p>AIM<\/jats:p>\n          <jats:p>To present in detail the \u201cElectronic Pediatrician (EPed)\u201d, a medical non-machine learning artificial intelligence (nml-AI) KBS in its prototype version created by the corresponding author (with database written in Romanian) that offers a physiopathology-based differential and positive diagnosis and treatment of ill children.<\/jats:p>\n          <jats:p>METHODS<\/jats:p>\n          <jats:p>EPed specifically focuses on the physiopathological reasoning of pediatric clinical cases. EPed has currently reached its prototype version 2.0, being able to diagnose 302 physiopathological macro-links (briefly named \u201cclusters\u201d) and 269 pediatric diseases: Some examples of diagnosis and a previous testing of EPed on a group of 34 patients are also presented in this paper.<\/jats:p>\n          <jats:p>RESULTS<\/jats:p>\n          <jats:p>The prototype EPed can currently diagnose 269 pediatric infectious and non-infectious diseases (based on 302 clusters), including the most frequent respiratory\/digestive\/renal\/central nervous system infections, but also many other non-infectious pediatric diseases like autoimmune, oncological, genetical diseases and even intoxications, plus some important surgical pathologies.<\/jats:p>\n          <jats:p>CONCLUSION<\/jats:p>\n          <jats:p>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 \u201cclusters\u201d 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.<\/jats:p>","DOI":"10.5662\/wjm.v15.i3.100903","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:50:31Z","timestamp":1741222231000},"source":"Crossref","is-referenced-by-count":0,"title":["\u201cElectronic Pediatrician\u201d, a non-machine learning prototype artificial intelligence software for pediatric computer-assisted pathophysiologic diagnosis \u2015 general presentation"],"prefix":"10.5662","volume":"15","author":[{"given":"Andrei-Lucian","family":"Dr\u0103goi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roxana-Maria","family":"Neme\u0219","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2060","published-online":{"date-parts":[[2025,9,20]]},"reference":[{"key":"B1","unstructured":"Sowa JF.   Knowledge Representation: Logical, Philosophical, and Computational Foundations (1st ed.). Available from: https:\/\/books.google.ro\/books\/about\/Knowledge_Representation.html?id=dohQAAAAMAAJ&redir_esc=y"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2018.06.014"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1001\/archpedi.1975.02120390033007"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1001\/archpedi.1995.02170250077014"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0335-9"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1097\/CM9.0000000000000563"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1177\/0300060520945141"},{"key":"B8","unstructured":"Jackson P.   Introduction to Expert Systems (book, 3rd ed, 1998). Addison Wesley. Available from: https:\/\/books.google.ro\/books\/about\/Introduction_to_Expert_Systems.html?id=9rJQAAAAMAAJ&redir_esc=y"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1001\/jama.1987.03400010071030"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1300\/J115v17n02_02"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2010.09.004"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1515\/dx-2017-0045"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1007\/s11606-011-1804-8"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1136\/jamia.1996.96310634"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2023.105169"}],"container-title":["World Journal of Methodology"],"original-title":[],"link":[{"URL":"https:\/\/www.wjgnet.com\/2222-0682\/full\/v15\/i3\/100903.htm","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.wjgnet.com\/2222-0682\/full\/v15\/i3\/100903.htm","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:51:28Z","timestamp":1741222288000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.wjgnet.com\/2222-0682\/full\/v15\/i3\/100903.htm"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,20]]},"references-count":15,"journal-issue":{"issue":"3"},"alternative-id":["100903"],"URL":"https:\/\/doi.org\/10.5662\/wjm.v15.i3.100903","relation":{},"ISSN":["2222-0682"],"issn-type":[{"value":"2222-0682","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9,20]]}}}