Artificial intelligence (AI) has the potential to enable more precise, efficient, and reproducible interpretation of medical imaging data to improve patient care in paediatric neuro-oncology. Paediatric brain tumours present distinct histopathological, molecular, and clinical challenges that require tailored AI solutions. Recent advances have led to paediatric-specific AI tools for tumour segmentation, treatment response evaluation, recurrence prediction, toxicity assessment, and integrative…
[Policy Review] Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 1: review of the current state of the art
The Lancet Oncology | | Benjamin H Kann, Arastoo Vossough, Sarah C Brüningk, Ariana M Familiar, Mariam Aboian, Marius George Linguraru, Kristen W Yeom, Susan M Chang, Darren Hargrave, David Mirsky, Phillip B Storm, Raymond Y Huang, Adam C Resnick, Michael Weller, Sabine Mueller, Michael Prados, Andrew C Peet, Javier E Villanueva-Meyer, Spyridon Bakas, Jason Fangusaro, Ali Nabavizadeh, Anahita Fathi Kazerooni, Response Assessment in Pediatric Neuro-Oncology (RAPNO) group
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