Single and Mitochondrial Gene Inheritance Disorder Prediction Using Machine Learning

One of the most difficult jobs in post-genomic age is identifying a genetic disease from massive amount data. Furthermore, complicated has very diverse genotype, making it challenging to find markers. This process since must be completed effectively and efficiently. research article focuses largely on which patients are more likely have disorder based numerous medical parameters. Using patient’s history, we used prediction algorithm that predicts if patient diagnosed with disorder. To predict categorize disease, utilize several deep machine learning techniques such as Artificial neural network (ANN), K-nearest neighbors (KNN), Support vector (SVM). enhance accuracy predicting any patient, highly efficient approach was utilized control how model can used. approaches performed. The productive tool provides precise efficiency. simulation results demonstrate by using proposed ANN, achieve highest performance 85.7%, 84.9%, 84.3% training, testing validation respectively. will undoubtedly transform give real competitive strategy save patients’ lives.