Exploring Machine Learning to Predict Brain Tumour Disease

The demand of AI is increasing day by day in the medical field. Machine Learning (ML) is subset of AI. ML has become popular tool and widely used to detect several medical diseases at higher accuracy. Promising accuracy of ML algorithms depend on training of digital images like CT, MRI, X-rays etc. In this paper, CNN model is proposed to classify brain tumour into malignant and non-malignant class and comparative study using diverse ML algorithm is conducted and their accuracy is compared. This paper explores role of ML in clinical diagnosis, accurate prediction and clinical analysis regarding brain tumour disease based on various brain tumour dataset like figshare, brats, Kaggle. Proposed CNN model has achieved 98 % promising accuracy.