Published Paper Details:

Brain Haemorrhage isthe eruption of the brain arteries due to high blood pressure or blood clotting that could cause a traumatic injury or death.Traumatic brain damage or death may occur when the brain's arteries burstopen as a result of hypertension or blood coagulation. This is a life threatening situation that requires a doctor with extensive training and expertise to pinpoint the source of the internal hemorrhaging and provide treatment without delay. This research proposes the Yolo model, a deeplearning algorithm, for the purpose of classifying brain hemorrhages. To improve the deep learning models' accuracy and processing capability, we utilize the dataset of head CT scan pictures. Since large datasets are oftenunavailable in critical situations, this work primarily aims to apply deep learning's abstraction capacity to a smaller selection of photos. Theperformance of the proposed approach will be analysed in terms of accuracy,precision, sensitivity and F1 score. Analyses comparing the Yolo model tobalanced and unbalanced datasets further assess the experimental outcomes.By intentionally destabilising the dataset and achieving maximum precision,yolo is able to provide promising findings.