102 citations · 104 across the 3 of their papers we have counts for
3 papers
Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium
Haris Shuaib, Gareth J Barker, Peter Sasieni +16
Objective: To report imaging protocol and scheduling variance in routine care of glioblastoma patients in order to demonstrate challenges of integrating deep-learning models in gli…
Machine Learning and Glioblastoma: Treatment Response Monitoring Biomarkers in 2021
Thomas Booth, Bernice Akpinar, Andrei Roman +10
The aim of the systematic review was to assess recently published studies on diagnostic test accuracy of glioblastoma treatment response monitoring biomarkers in adults, developed…
Machine learning and glioma imaging biomarkers
Thomas Booth, Matthew Williams, Aysha Luis +3
Aim: To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring. Materials an…