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Utility of pre-treatment FDG PET/CT–derived machine learning models for outcome prediction in classical Hodgkin lymphoma

OBJECTIVES: Relapse occurs in ~20% of patients with classical Hodgkin lymphoma (cHL) despite treatment adaption based on 2-deoxy-2-[(18)F]fluoro-d-glucose positron emission tomography/computed tomography response. The objective was to evaluate pre-treatment FDG PET/CT–derived machine learning (ML) m...

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Detalles Bibliográficos
Autores principales:	Frood, Russell, Clark, Matt, Burton, Cathy, Tsoumpas, Charalampos, Frangi, Alejandro F., Gleeson, Fergus, Patel, Chirag, Scarsbrook, Andrew
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2022
Materias:	Imaging Informatics and Artificial Intelligence
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403224/ https://www.ncbi.nlm.nih.gov/pubmed/36006428 http://dx.doi.org/10.1007/s00330-022-09039-0

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