An Exploration: Deep Learning-Based Hybrid Model for Automated Diagnosis and Classification of Brain Tumor Disorder

Reproduction of abnormal tissues within the brain due to any damage can cause major concerns for an individuals’ health which can be identified by radiologists after examining cell structure of brain that clarifies whether it belongs to benign, i.e., non-cancerous or malign, i.e., cancerous. Although it cannot be treated properly, identifying abnormal growth of tissue at very initial phase can definitely help in preventing from major issues. Most of the researchers described automated brain tumor diagnosing methods in their publications which also received the most attention to provide significant contribution in the healthcare. Authors achieved the highest accuracy of 93.72% via deploying deep learning-based models while predicting brain tumor disease as these models have ability to analyze vast amount of data and able to extract significant features accurately and efficiently as compared to the existing approaches in short duration to provide improved patient outcomes and timely treatment in the healthcare.