Cargando…
Learning Medical Materials From Radiography Images
Deep learning models have been shown to be effective for material analysis, a subfield of computer vision, on natural images. In medicine, deep learning systems have been shown to more accurately analyze radiography images than algorithmic approaches and even experts. However, one major roadblock to...
Autores principales: | Molder, Carson, Lowe, Benjamin, Zhan, Justin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8320745/ https://www.ncbi.nlm.nih.gov/pubmed/34337390 http://dx.doi.org/10.3389/frai.2021.638299 |
Ejemplares similares
-
Bone fracture detection—Can artificial intelligence replace doctors in orthopedic radiography analysis?
por: Hussain, Aariz, et al.
Publicado: (2023) -
Trends and hotspots in research on medical images with deep learning: a bibliometric analysis from 2013 to 2023
por: Chen, Borui, et al.
Publicado: (2023) -
From ECG signals to images: a transformation based approach for deep learning
por: Naz, Mahwish, et al.
Publicado: (2021) -
Predicting Tissue-Specific mRNA and Protein Abundance in Maize: A Machine Learning Approach
por: Cho, Kyoung Tak, et al.
Publicado: (2022) -
Deep Ensemble Learning for Retinal Image Classification
por: Ho, Edward, et al.
Publicado: (2022)