9 citations · 9 across the 3 of their papers we have counts for
3 papers
Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors
Nicolas Raymond, Maxime Caru, Hakima Laribi +6
Acute lymphoblastic leukemia is the most frequent pediatric cancer. Approximately two third of survivors develop one or more health complications known as late adverse effects foll…
Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images
Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad +8
This paper presents an overview of the second edition of the HEad and neCK TumOR (HECKTOR) challenge, organized as a satellite event of the 24th International Conference on Medical…
Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer
Martin Vallières, Emily Kay-Rivest, Léo Jean Perrin +9
Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk…