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Disease Prediction System Using Image Processing and Machine Learning in COVID-19

Disease Prediction System Using Image Processing and Machine Learning in COVID-19

Sonal Raju Shilimkar (MKSSS's Cummins College of Engineering, India), Varsha Pimprale (MKSSS's Cummins College of Engineering, India), and Chhaya R. Gosavi (MKSSS's Cummins College of Engineering, India)
Copyright: © 2022 |Pages: 22
DOI: 10.4018/978-1-7998-9121-5.ch007
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Abstract

Diseases such as cancers, pneumonia, and COVID really need to be detected at the right time. If early detection and treatment of such diseases get started as soon as possible, then, probably, patients can be cured completely. Early detection of such diseases is very important, and early-stage imaging can be done based on x-rays, mammography reports, or pathological reports. The purpose of this system is to provide predictions for the different major diseases like cancer and some general occurring diseases. Image processing along with machine learning techniques made it possible to find the chances of occurrence of cancer/tumor/lump in the human body. As per the predicted probability, a patient can make an early decision by discussing it with doctors. The system will predict the most possible disease based on the given symptoms and precautionary measures required to avoid the progression of disease. It will also help doctors analyze the pattern of presence of diseases in the society.
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Introduction

Evaluation of technology in the healthcare system makes life more convenient in detecting and treating disease. Nowadays, data or medical records are easier to collect and store. Using this data technology, one can easily detect some critical health issues at an early stage. Machine Learning algorithms and image processing techniques show fundamental potential in detecting multiple major diseases like cancer, pneumonia, diabetes and many others. Image processing plays an important role in visualising disease which makes it convenient to doctors and patients to view internal diseases.

Prediction of major and minor diseases is vital for the early detection of health threats. Such diseases can affect health majorly. Early identification of diseases like cancer, pneumonia is important so that patients and doctors can make early decisions about treatment. Using the latest technology trends including image processing and machine learning makes this task easier. Using this technology one can easily identify disease. Machine learning and Image processing gives more accurate results than naked eye and predicts within fraction of seconds.

This proposed system is web application which will predict disease:

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    Based on symptoms.

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    Based on image reports (like x-ray, mammography, MRI, etc)

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    Based on given diagnosis report parameter values.

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    Suggest nearby specialists based on predicted disease.

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Background

It is estimated that more than 70% of people are prone to body diseases like cancer, viral infections and many other general/major diseases. Around 30% of the population succumbs to death because of ignoring the early general body symptoms. Hence it is important to identify and predict disease at the earliest stage to avoid any unwanted casualties.

The authors did some literature review about the prediction of disease and observed the pros and cons of these highly correlated systems are discussed below.

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