Machine Learning in the Differentiation of Soft Tissue Neoplasms: Comparison of Fat-Suppressed T2WI and Apparent Diffusion Coefficient (ADC) Features-Based Models

Machine learning has been widely used in the characterization of tumors recently. This article aims to explore the feasibility of the whole tumor fat-suppressed (FS) T2WI and ADC features-based least absolute shrinkage and selection operator (LASSO)-logistic predictive models in the differentiation...

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Detalles Bibliográficos
Autores principales: Hu, Peian, Chen, Lei, Zhou, Zhengrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554992/
https://www.ncbi.nlm.nih.gov/pubmed/34545474
http://dx.doi.org/10.1007/s10278-021-00513-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554992/
https://www.ncbi.nlm.nih.gov/pubmed/34545474
http://dx.doi.org/10.1007/s10278-021-00513-7

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