Cargando…
Attention Deep Feature Extraction from Brain MRIs in Explainable Mode: DGXAINet
Artificial intelligence models do not provide information about exactly how the predictions are reached. This lack of transparency is a major drawback. Particularly in medical applications, interest in explainable artificial intelligence (XAI), which helps to develop methods of visualizing, explaini...
Autor principal: | Taşcı, Burak |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000758/ https://www.ncbi.nlm.nih.gov/pubmed/36900004 http://dx.doi.org/10.3390/diagnostics13050859 |
Ejemplares similares
-
A Pyramid Deep Feature Extraction Model for the Automatic Classification of Upper Extremity Fractures
por: Kaya, Oğuz, et al.
Publicado: (2023) -
Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs
por: Huang, Xiaona, et al.
Publicado: (2023) -
Headache classification and automatic biomarker extraction from structural MRIs using deep learning
por: Rahman Siddiquee, Md Mahfuzur, et al.
Publicado: (2022) -
Deep Multi-Branch CNN Architecture for Early Alzheimer’s Detection from Brain MRIs
por: Mandal, Paul K., et al.
Publicado: (2023) -
Automatic biometry of fetal brain MRIs using deep and machine learning techniques
por: She, Jiayan, et al.
Publicado: (2023)