Explore The Application Of Machine Learning Algorithms To Analyze Genetic And Clinical Data To Tailor Treatment Plans For Individual Patients

Abstract

In light of the growing body of research in the field of medicine pertaining to machine learning. There are already an increasing number of research that have adapted it to tailored medicine, such as monitoring drug concentrations and predicting bad reactions. Unlike the more conventional approaches to population pharmacokinetic modeling, machine learning is able to assess a significant amount of data pertaining to medications that are used in the actual world. Machine learning may more precisely forecast blood drug concentration and drug dose through multi-level mining of the data. This allows for the construction of a more practical tailored medicine model, an improvement in the degree of clinical precision medication, and a reduction in the number of adverse reactions that occur. The purpose of this article is to give both a theoretical foundation and a technical support for clinical precision medicine by reviewing the research that has been conducted on machine learning in the field of customized medicine.