• Chanchal Sahebrao Gaikwad

An Ischemic stroke is a curse to the mankind which eventually leaves barely few hours to give proper treatment before it could paralyze the body. So in this scenario, it is very important that in the intensive care unit immediate and accurate treatment should be given to the patient so that he/she could not go into a deep stroke. So in the ICU, there is very less time is there in the hands of the doctor to take the right decision about the medicines and other procedures which eventually take the big step to save the patient's life. So it is very important to learn the all aspects of the emergency procedure before any circumstances arise. So Machine learning is the boon to this kind of scenario where it gives the best option to learn the past treatment history and evolved with the precise treatment technique. So proposed methodology put forward an idea of using past treatment dataset using K nearest neighbor and Fuzzy ANN techniques which is powered with Random forest algorithm to produce the best possible prediction outcomes for ischemic stroke patients.

Ischemic Stroke, K- Nearest Neighbor, Random Forest.

"Investigation of ischemic stroke patient Outcomes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.104-107, December-2018, Available :http://www.jetir.org/papers/JETIR1812916.pdf

"Investigation of ischemic stroke patient Outcomes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp104-107, December-2018, Available at : http://www.jetir.org/papers/JETIR1812916.pdf