Brain tumor detection using artificial convolutional neural networks
arXiv:2207.11248v1h-index: 7
Originality Synthesis-oriented
AI Analysis
This addresses brain tumor detection for medical diagnosis, but it appears incremental as it applies an existing CNN method to a specific dataset.
The paper tackled brain tumor classification from NMR images using a convolutional neural network, achieving 100% training accuracy and 96% precision in evaluation.
In this paper, a convolutional neural network (CNN) was used to classify NMR images of human brains with 4 different types of tumors: meningioma, glioma and pituitary gland tumors. During the training phase of this project, an accuracy of 100% was obtained, meanwhile, in the evaluation phase the precision was 96%.