A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodulesResearch in context

Summary: Background: Large lung nodules (≥15 mm) have the highest risk of malignancy, and may exhibit important differences in phenotypic or clinical characteristics to their smaller counterparts. Existing risk models do not stratify large nodules well. We aimed to develop and validate an integrate...

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Detalhes bibliográficos

Principais autores:	Benjamin Hunter, Mitchell Chen, Prashanthi Ratnakumar, Esubalew Alemu, Andrew Logan, Kristofer Linton-Reid, Daniel Tong, Nishanthi Senthivel, Amyn Bhamani, Susannah Bloch, Samuel V. Kemp, Laura Boddy, Sejal Jain, Shafick Gareeboo, Bhavin Rawal, Simon Doran, Neal Navani, Arjun Nair, Catey Bunce, Stan Kaye, Matthew Blackledge, Eric O. Aboagye, Anand Devaraj, Richard W. Lee
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2022-12-01
coleção:	EBioMedicine
Assuntos:	Lung cancer Radiomics Early diagnosis Machine learning Lung nodules Deep learning
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2352396422005266
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