Development of a novel deep learning method that transforms tabular input variables into images for the prediction of SLD

Abstract Steatotic liver disease (SLD), formerly named fatty liver disease, has a prevalence estimated at 30–38% in adults. Detection of SLD is important, since prompt initiation of treatment can stop disease progression, lead to a reduction in adverse outcomes, and reduce the economic burden associ...

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Bibliographic Details
Main Authors:	Gabriel Cubillos, Javier Perez-Valenzuela, Herman Aguirre, Luz Martínez, Lorena Castro, Gabriel Mezzano, Claudio A. Perez
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-07-01
Series:	Scientific Reports
Subjects:	Steatotic liver disease (SLD) SLD prediction Fatty liver disease (FLD) Machine learning models Deep learning Convolutional neural networks
Online Access:	https://doi.org/10.1038/s41598-025-12900-z
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Development of a novel deep learning method that transforms tabular input variables into images for the prediction of SLD

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