Multiclass classification models for Personalized Medicine prediction based on patients Genetic Variants

Establishing a diagnosis through genome sequencing will give potential advantages to patients. Genetic knowledge is very prominent in detecting patients' personalized disease syndrome. Hence, diagnostic sequencing is being used progressively. Various machine learning models have been used for predicting cancer categories supported by data with the genome sequence. Predicting the correct variant for patients’ diagnosis will increase the diagnostic rate. Genetic testing will disrupt many diseases like cancer and any other genetic disease. This research work aims at providing a machine learning-based model using genome data to acquire guidance towards personalized medication.