Open AccessShort Training Significantly Improves Ganglion Cell Detection Using an Algorithm-Assisted Approach
Author(s) -
Ariel Greenberg,
Benzion Samueli,
Ibrahim Fahoum,
Shai Farkash,
Orli Greenberg,
Valentina Zemser-Werner,
Edmond Sabo,
Rami R. Hagege,
Dov Hershkovitz
Publication year - 2022
Publication title -
archives of pathology and laboratory medicine (1976)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 117
eISSN - 1543-2165
pISSN - 0003-9985
DOI - 10.5858/arpa.2021-0481-oa
Subject(s) - medical diagnosis , medicine , context (archaeology) , false positive paradox , session (web analytics) , presentation (obstetrics) , algorithm , task (project management) , machine learning , pathology , computer science , radiology , management , world wide web , economics , paleontology , biology
Medical education in pathology relies on the accumulation of experience gained through inspection of numerous samples from each entity. Acquiring sufficient teaching material for rare diseases, such as Hirschsprung disease (HSCR), may be difficult, especially in smaller institutes. The current study makes use of a previously developed decision support system using a decision support algorithm meant to aid pathologists in the diagnosis of HSCR.