Multi-Class Drug Classification Using Machine Learning Models
Y.Venkatalakshmi, Kummara Kasinatha, Chintha Maruthi, Kudapu Mahesh Babu, Bodi Lakshmi Narayana, Kundanakurti Anil
In the world of medicine, drug classification holds immense importance as it helps determine the most
suitable drugs for patients based on their unique characteristics and medical history. The dataset
containing various features plays a vital role in assessing which drugs are best suited for individuals.
This process is known as multi-class drug classification, where drugs are categorized into different
classes based on their specific uses and therapeutic effects. Traditionally, drug classification has been
carried out through manual or rule-based approaches, where physicians and medical experts rely on
their knowledge and experience to prescribe drugs based on patient attributes. However, this method
can be time-consuming and may not be efficient when dealing with a large number of drugs and patients.
That's where machine learning comes in to revolutionize the process.
