Disease Detection System: Supervised Learning to Detect Diseases

Abstract

A type of machine learning called supervised learning uses labelled training data to teach computers how to forecast the outcome. The labeled data denotes that some input data has been already marked with the correct output. This training data acts as a supervisor, guiding the machines to accurately forecast the output, akin to a teacher supervising a student. The objective of supervised learning is to provide a machine-learning model with correct input and output data. The method seeks a mapping function that connects the input variable (x) to the output variable (y). The spread of numerous diseases through common means such as air and touch has become a significant concern, particularly during the COVID-19 pandemic. The Disease Detection System employs supervised learning to address this challenge by detecting diseases with just a few clicks on the software. In the future, the input-based prediction system could be extended to an im-age-based prediction system.