Predicting Medical Therapy Using a Computational Intelligence Method

Methods of computational intelligence are proving to be effective assistance for physicians and other medical personnel, boosting objectivity when making diagnostic and treatment decisions while also reducing decision time. Using computational intelligence tools to predict three stroke variables surgery required, rehabilitation, and days of rehabilitation required, we will have a reference point, and our overall goal for future research is to follow-up on the subjects to help them return to their normal lives faster and at a lower cost. The development of a Database Acknowledgment (DBK) using Neural Network (NN) methods is proposed to anticipate the three characteristics mentioned: surgery, treatment, and days of rehabilitation. The goal is to use three different tools to develop an ideal neural network setup utilising the actual information available: One is manual, another is semi-automatic, and the third is based on Neuro-Intelligence. The prediction error of our proposed solution must be as low as possible.

Author(s): Rowby Hutia

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