Abstract

The paper brings forward a novel point of view to human disease prediction along with drug recommendation utilizing machine learning (ML) techniques. With the increasing availability of healthcare data, there is a growing need for efficient methods to predict diseases accurately and recommend suitable treatments. Our study addresses this challenge by leveraging ML algorithms to analyse patient symptoms, medical history, and demographic information to predict the likelihood of various diseases. Additionally, our research aim to give personalized drug recommendation to patients on their predicted diseases. By integrating ML models with healthcare data, our system can offer tailored treatment plans that consider individual patient characteristics and medical histories. We propose a drug recommendation system that takes into account multi-disease scenarios, providing accurate drug recommendations to healthcare professionals. Our approach not only enhances the efficiency of disease diagnosis and treatment selection but also contributes to improved patient outcomes and healthcare delivery. By harnessing the power of ML, our research offers a promising solution to the complex challenges in healthcare.