Cargando…
Endoscopy-based IBD identification by a quantized deep learning pipeline
BACKGROUND: Discrimination between patients affected by inflammatory bowel diseases and healthy controls on the basis of endoscopic imaging is an challenging problem for machine learning models. Such task is used here as the testbed for a novel deep learning classification pipeline, powered by a set...
Autores principales: | Datres, Massimiliano, Paolazzi, Elisa, Chierici, Marco, Pozzi, Matteo, Colangelo, Antonio, Dorian Donzella, Marcello, Jurman, Giuseppe |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675910/ https://www.ncbi.nlm.nih.gov/pubmed/38001537 http://dx.doi.org/10.1186/s13040-023-00350-0 |
Ejemplares similares
-
Automatically detecting Crohn’s disease and Ulcerative Colitis from endoscopic imaging
por: Chierici, Marco, et al.
Publicado: (2022) -
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification
por: Chicco, Davide, et al.
Publicado: (2023) -
Endoscopy in IBD: When and How?
por: Daperno, Marco
Publicado: (2023) -
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation
por: Chicco, Davide, et al.
Publicado: (2021) -
Future of Endoscopy in Inflammatory Bowel Diseases (IBDs)
por: Agrawal, Laksh S, et al.
Publicado: (2022)