• Ms.Chanchal Sahebrao Gaikwad
• Prof.Prashant B Jawalkar

The sudden attack of Ischemic strokes always astonishes the patient, doctor and dear ones to the patient. The proper treatment of the ischemic stroke patient hidden in the fact of the severity of the stroke that the patient is suffering for the moment. Most of the time due to unaware of the severity of the stroke the Doctors follow non required procedures to cure the same using trial and error method, which eventually results in permanent damage of the organs or even as fetal. So it is very important to estimate the functional outcomes of the ischemic stroke patient based on some vital parameters of the patient's health. Some finger counting methodologies are existed to deal with this, because the complexity of the stroke is associated with the numerous attributes that reveal many secrets about the outcome possibilities. As a tiny step towards this proposed model incorporates some finest blends of the machine learning techniques which are enriched in the unique way to get the best functional outcomes for the ischemic Stroke patients. The proposed model uses the K - nearest neighbor algorithm which is powered with the linear regression model to yield the best proportional clusters. Further Fuzzy ANN and Random forest algorithms create a proper learning mechanism model to classify the functional outcomes for the ischemic dataset.

Fuzzy ANN, Random Forest, Linear Regression, K-Nearest neighbor, Ischemic Stroke

"Enriching Functional outcomes in Ischemic Stroke Patients using Fuzzy ANN and Random Forest", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.117-122, June 2019, Available :http://www.jetir.org/papers/JETIR1906O16.pdf

"Enriching Functional outcomes in Ischemic Stroke Patients using Fuzzy ANN and Random Forest", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp117-122, June 2019, Available at : http://www.jetir.org/papers/JETIR1906O16.pdf