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Article . 2023
License: CC BY NC
Data sources: ZENODO
ZENODO
Article . 2023
License: CC BY NC
Data sources: Datacite
ZENODO
Article . 2023
License: CC BY NC
Data sources: Datacite
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Development of a Novel Machine Learning Framework For Brain Tumors Using Explainable Ai And Deep Learning

Authors: Rashi Bhave; Yati Kale; Dr. Sharmishta Desai; Yuvraj Khare;

Development of a Novel Machine Learning Framework For Brain Tumors Using Explainable Ai And Deep Learning

Abstract

Majorly in cancers related to Central Nervous System, 85% to 90% of all initial central nervous system (CNS) tumors are brain tumors. Tumors can be detected using multiple state-of-the-art technologies. We studied 6251 MRI scans which contained images for Glioma, Meningioma, Pituitary tumors and no tumor. We built a CNN (Convolutional Neural Networks) model which was iterated for 5 epochs, with overall test accuracy of 83.1%, a training loss of 0.44 and a validation loss of 0.41 for 1200 test images. 225 images were correctly classified as glioma and 195 as meningioma. There are 248 images for no tumor and 342 images for pituitary. 190 images were classified incorrectly. We further used the Explainable AI model LIME to understand the prediction of the CNN model.

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Keywords

Deep Learning, Brain Tumor, CNN

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green