Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm

2020/05/30 by Gopal S. Tandel, Antonella Balestrieri, Tanay Jujaray +4 · 253 citations
Medicine · Neuroscience · #Artificial intelligence #Artificial neural network #Bayes' theorem #Brain Tumor Detection and Classification #Computer science #Convolutional neural network #Decision tree #Deep learning #Glioma Diagnosis and Treatment #Gold standard (test) #Grading (engineering) #Machine learning #Magnetic resonance imaging #Medicine #Multiclass classification #Naive Bayes classifier #Pattern recognition (psychology) #Radiology #Radiomics and Machine Learning in Medical Imaging #Support vector machine #Transfer of learning

paper · doi:10.1016/j.compbiomed.2020.103804

published in Computers in Biology and Medicine 122, 103804 (Elsevier BV)

openalex publication_date 2020/05/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Citations

• ImageNet classification with deep convolutional neural networks
• The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary

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