Early Detection of Brain Stroke using Machine Learning Techniques

Early Detection of Brain Stroke using Machine Learning Techniques

Bhoomika R S1, Aishwarya J Annigeri2, Himaja Desiraju3, Harsh Kumar Goswami4, Prof. Vani K.A 5

Department of Information Science and Engineering, Dayananda Sagar College of Engineering

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Abstract - As in line with the WHO, stroke is the principle source of death and incapability round the world . It is a clinical condition that causes brain damage by way of tearing blood vessels.It is able to likewise take place whilst the development of blood and unique dietary supplements to the cerebrum is disturbed. Most of exploration has targeted on foreseeing breathing screw ups, however not very many examinations have focused on the gamble of a mind assault. Numerous device learning fashions are being advanced with this in mind and are expecting the possibility of a mind stroke. Various physiological elements were used on this paper to educate various fashions for correct prediction using 10 machine studying algorithms inclusive of logistic regression, decision tree type, k-nearest acquaintances, random forest classifier, svm ,adaboost classifier,bernoullinb,mlp,bagging classifier and lgbm.

Key Words: stroke,logisticregression,decisiontree,knn,svm,ran domforest,adaboost,bernoullinb,mlp,bagging,lgbm,flask