首页|Data on Artificial Intelligence Reported by Mohammad Zafer Khaliki and Colleagues (Brain tumor detection from images and comparison with transfer learning methods and 3-layer CNN)
Data on Artificial Intelligence Reported by Mohammad Zafer Khaliki and Colleagues (Brain tumor detection from images and comparison with transfer learning methods and 3-layer CNN)
扫码查看
点击上方二维码区域,可以放大扫码查看
原文链接
NETL
NSTL
New research on Artificial Intelligence is the subject of a report. According to news reporting originating in Istanbul, Turkey, by NewsRx journalists, research stated, “Health is very important for human life. In particular, the health of the brain, which is the executive of the vital resource, is very important.” The news reporters obtained a quote from the research, “Diagnosis for human health is provided by magnetic resonance imaging (MRI) devices, which help health decision makers in critical organs such as brain health. Images from these devices are a source of big data for artificial intelligence. This big data enables high performance in image processing classification problems, which is a subfield of artificial intelligence. In this study, we aim to classify brain tumors such as glioma, meningioma, and pituitary tumor from brain MR images. Convolutional Neural Network (CNN) and CNN-based inception-V3, EfficientNetB4, VGG19, transfer learning methods were used for classification. F-score, recall, imprinting and accuracy were used to evaluate these models. The best accuracy result was obtained with VGG16 with 98%, while the F-score value of the same transfer learning model was 97%, the Area Under the Curve (AUC) value was 99%, the recall value was 98%, and the precision value was 98%.”
IstanbulTurkeyEurasiaArtificial IntelligenceBrain CancerCancerEmerging TechnologiesHealth and MedicineMachine LearningOncology