Cargando…
A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering
An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data are presented as images, identifying properties that characterize a disease b...
Autores principales: | Thunold, Håvard Horgen, Riegler, Michael A., Yazidi, Anis, Hammer, Hugo L. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670034/ https://www.ncbi.nlm.nih.gov/pubmed/37998548 http://dx.doi.org/10.3390/diagnostics13223413 |
Ejemplares similares
-
Towards the Neuroevolution of Low-level artificial general intelligence
por: Pontes-Filho, Sidney, et al.
Publicado: (2022) -
Predicting an unstable tear film through artificial intelligence
por: Fineide, Fredrik, et al.
Publicado: (2022) -
A deep explainable artificial intelligent framework for neurological disorders discrimination
por: Shahtalebi, Soroosh, et al.
Publicado: (2021) -
Explainable vs. interpretable artificial intelligence frameworks in oncology
por: Bertsimas, Dimitris, et al.
Publicado: (2023) -
An explainable artificial intelligence framework for risk prediction of COPD in smokers
por: Wang, Xuchun, et al.
Publicado: (2023)