Cargando…
Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging
One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply oversampling strategies in an attempt to balance the...
Autores principales: | Teh, Kevin, Armitage, Paul, Tesfaye, Solomon, Selvarajah, Dinesh, Wilkinson, Iain D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737960/ https://www.ncbi.nlm.nih.gov/pubmed/33320890 http://dx.doi.org/10.1371/journal.pone.0243907 |
Ejemplares similares
-
Deep Learning Classification of Treatment Response in Diabetic Painful Neuropathy: A Combined Machine Learning and Magnetic Resonance Neuroimaging Methodological Study
por: Teh, Kevin, et al.
Publicado: (2022) -
Central Pain Processing in Chronic Chemotherapy-Induced Peripheral Neuropathy: A Functional Magnetic Resonance Imaging Study
por: Boland, Elaine G., et al.
Publicado: (2014) -
Preservation of thalamic neuronal function may be a prerequisite for pain perception in diabetic neuropathy: A magnetic resonance spectroscopy study
por: Gandhi, Rajiv, et al.
Publicado: (2023) -
Somatosensory network functional connectivity differentiates clinical pain phenotypes in diabetic neuropathy
por: Teh, Kevin, et al.
Publicado: (2021) -
Painful and Painless Diabetic Neuropathies: What Is the Difference?
por: Shillo, Pallai, et al.
Publicado: (2019)