Investigation of artificial intelligence methods for detecting brain tumor

N. Vaishnavi *, R. Haripriya, K. Mahasuwetha, B. Kabilesh, D. Sajith Ramana, N. Manikandan, M. Gokul, J. Benito Sam Kumar, D. Iswariya and R. Sowmiya

Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, India.
 
Research Article
International Journal of Science and Research Archive, 2024, 11(02), 1263–1270.
Article DOI: 10.30574/ijsra.2024.11.2.0562
 
Publication history: 
Received on 23 February 2024; revised on 03 April 2024; accepted on 06 April 2024
 
Abstract: 
Brain tumors are debilitating, and can cause a shorter life in case not analyzed early adequately.
Fake bits of knowledge (AI) can offer help to overcome the issue of bring and time in diagnosing brain tumors. There are two sorts of Brain tumor classification: pituitary and glioma The proposed models are associated with a dataset of 1,800 MRI pictures comprising two classes of investigation; glioma tumors and pituitary tumors. To realize a reasonable treatment course of action, classification of brain tumors is an incredibly fundamental step after detection. A dataset comprising 1,800 MRI pictures comprising two classes of investigation, pituitary tumor, and glioma tumors, was utilized to classify brain tumors: pituitary tumor and glioma tumor. It is essential to classify brain tumors after area in arrange to be able to characterize a successful treatment arrangement. This term paper focuses on amplifying the level and viability of utilizing AI Algorithms. In afterward a long time, the utilization of fake experiences (AI) is surging through all circles of science, and no address, it is revolutionizing the field of neurology. The application of AI in helpful science has made brain disease estimates and areas more exact and correct.
 
Keywords: 
Brain Tumor; MR Images; Classification; Methodology; Artificial Intelligence
 
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