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2021-180 Smart Assistant to ease the process of COVID-19 and Pneumonia disease detection
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2021-180
2021-180 Smart Assistant to ease the process of COVID-19 and Pneumonia disease detection
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32106ed2
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32106ed2
authored
Apr 17, 2021
by
Akalanka B. A. IT18114836
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@@ -200,4 +200,41 @@ emotion/pain from “slightly” to “extremely.”
Analyze the severity level of the patient considering about all the data that
gathered via the question answering system. According to the severity level
patient will be advised what he/she can do as the next step and if its possible
we suppose to give medical recommendation.
we suppose to give medical recommendation.
**IT18125962 Nimantha W.A.R**
Covid-19 has become a major lung-related disease daily with the current epidemic.
Therefore, it is essential to identify patients as early as possible and to
distinguish Covid-19 patients from other patients with lung-related diseases
such as pneumonia. The main problem with doing this is the time it takes to get
the preliminary results from the existing test methods. Although there are
methods available for fast counter results call PCR.
Most of people go backward to do PCR test. Because they tell it is pain full and
it is risk to spread corona. Therefore, people requests more accurate
things faster than PCR test.
Chest X-rays are a cheap and fast method used to diagnose lung-related diseases
such as pneumonia. This research focuses on the possibility of using X-rays and
CT scan of the chest and machine learning model use to identify Covid-19 and
distinguish them from other selected lung-related diseases using symptoms.
**Objectives**
Training three model and select model that have highest accuracy to predict risk
level and classify the covid-19 and covid-pneumonia using patient’s symptoms and
patient’s age and sex within this year.
*
To develop model for classify covid-19 and pneumonia
In this train machine learning model to classify covid-19 or pneumonia.
*
To improve accuracy of trained algorithm.
Algorithm should be trained and improved accuracy until come to expected accuracy.
*
To develop user friendly mobile application
In this objective develop a mobile application to collect symptoms and upload it
to the cloud for do the prediction and classification through the Machine
learning model.
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