Topological data analysis of thoracic radiographic images shows improved radiomics-based lung tumor histology prediction.

Vandaele, Robin; Mukherjee, Pritam; Selby, Heather Marie; Shah, Rajesh Pravin; Gevaert, Olivier

Vandaele, Robin; Mukherjee, Pritam; Selby, Heather Marie; Shah, Rajesh Pravin; Gevaert, Olivier.

Afiliación

Vandaele R; Department of Applied Mathematics, Computer Science and Statistics, Ghent University, 9000 Ghent, Belgium.
Mukherjee P; Data Mining and Modeling for Biomedicine, VIB Inflammation Research Center, 9052 Ghent, Belgium.
Selby HM; IDLab, Department of Electronics and Information Systems, Ghent University, Gent, Belgium.
Shah RP; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Gevaert O; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.

Patterns (N Y) ; 4(1): 100657, 2023 Jan 13.

Article en En | MEDLINE | ID: mdl-36699734

Palabras clave

computed tomography; computer vision; feature engineering; histology; radiology; supervised learning; topological data analysis

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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Patterns (N Y) Año: 2023 Tipo del documento: Article País de afiliación: Bélgica

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