Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review

Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review

<h3>Background </h3><p dir="ltr">Medulloblastoma is the most prevalent malignant brain tumor in children, requiring timely and precise diagnosis to improve clinical outcomes. Artificial Intelligence (AI) offers a promising avenue to enhance diagnostic accuracy and efficie...

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Main Author:	Hiba Alzoubi (18001609) (author)
Other Authors:	Alaa Abd-alrazaq (17058018) (author), Obada Almaabreh (22150096) (author), Rawan AlSaad (14159019) (author), Sarah Aziz (17541312) (author), Rukaya Al-Dafi (22150099) (author), Leen Abu Salih (22150102) (author), Leen Turani (22150105) (author), Sondos Albqowr (22150108) (author), Rawan Abu Tarbosh (22150111) (author), Batool Abu Alkishik (22150114) (author), Rafat Damseh (14440893) (author), Arfan Ahmed (17541309) (author), Hashem Abu Serhan (16003271) (author)
Published:	2025
Subjects:	Biomedical and clinical sciences Oncology and carcinogenesis Paediatrics Health sciences Health services and systems Medulloblastoma Brain tumors Artificial intelligence Histopathology Pediatric Systematic review
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