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Prediction and Detection of Infectious Disease through Machine Learning

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Manoj Kumar Singh, Dr. Kishan Pal Singh, Dr. Devendra Kumar
» doi: 10.31838/ecb/2023.12.si6.392


Infectious diseases are caused by organisms such as bacteria, viruses, fungi or parasites. They live in and on our bodies. Learning about infectious diseases provides a better understanding of human pathogens and the need for treatments and immunizations. These critical tasks may be carried out in a single clinic by infectious disease clinicians (disease physicians) with specialised training or with exceptional precision. Machine learning (ML) is employed in a variety of fields, including education and healthcare. It is utilised extensively in healthcare. In healthcare, ML is utilised to tackle a variety of challenges. Developing a machine learning model, training it on the dataset, and incorporating unique patient information may aid in prediction of the disease. The forecast result will be based on the data provided and so will be unique to that individual. Corona virus is an illness with no specific treatment. There are several therapies available for it, however there are no well-defined therapy processes. The goal of artificial intelligence (AI) is to replicate human cognitive processes. In this study we aimed to detect and predict of infectious disease, perform automated learning to predict and accurately detect infection and construct the model that can perform in real time aspects

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