# 2021-180 Smart Assistant to ease the process of COVID-19 and Pneumonia disease detection

2021-180 Smart Assistant to ease the process of Covid-19 and Pneumonia disease detection

**Main Objective**
Our main objective is to implement an application to diagnose pneumonia / Covid-19
in a short period of time and provide health advice and medical recommendations 
to patients. This application will reduce the cost of PCR testing and will give 
patients a higher accuracy result through the application. Patients will be 
asked about their symptoms, health history and counseling according to their 
severity. 
We suppose to screen x-rays and identify whether the patient suffering from 
pneumonia/covid-19. Main objective of screening x-ray images as it is a cheap
method compared to PCR tests. People must spend lots of money when doing a PCR 
test. So, one of over main objectives is reduce the cost for medical tests. 
If a patient considers not only the money, they spend but also the high accuracy
level, they can go for CT scan screening procedure. With that function we suppose
to maximize the accuracy level. According to the literature survey that we have 
done, CT scans gives high accurate results when compared to PCR tests. So, giving
a high accurate result will be full fill by this option that we have planned to do. 
Most important objective is after the patient is identified positive for 
pneumonia or covid-19 he/she should be guided to the medication or advices 
is a specific objective of this research. To advice the patient correctly we 
should first have a real understanding about the patient's current health 
condition and past health history. Otherwise, we cannot predict any advices.

**Main Research questions**
Covid-19 has become the foremost lung-related disease now a days with the
ongoing pandemic situation. Therefore, it has become vital to identify patients
as soon as possible and to differentiate Covid-19 patients from other patients 
with lung-related diseases like pneumonia. A major problem when doing this is 
the time it takes for the results to come out from the existing testing methods.
Even though methods that can generate faster results exist these methods are too
expensive for third-world countries like Sri Lanka. Sometimes the accuracy of a 
PCR test is in a low level compared to technologies like identifying covid-19 
using CT scan. When it comes to the technical side it takes lots of time to the
image uploading and processing part. Is one of the commonly found difficulties 
in existing applications.
Chest X-Rays are a cheap and faster method that is used to diagnose other
lung-related diseases like Pneumonia, covid-19. This research will be focused
on the possibility of using chest X-Rays to identify Covid-19 and differentiate
them from other selected lung-related diseases.

**IT18114836 Akalanka B.A**
The Covid - 19 epidemic has affected millions of people worldwide.
Today, millions of people have died, and many more are affected every day.
Due to the testing equipment's deficiency, many people go undiagnosed with 
COVID-19 in their early stages. In the early stages of this undiagnosed disease,
when people without physical symptoms encounter normal people, the virus can be 
transmitted from them to healthy people, and this chain continues. Reverse
transcription-polymerase chain reaction (RT-PCR) is the current approach to 
COVID-19 testing. Here the specimens of patients are collected through the nose
or throat and then sent to laboratories for diagnosis. Therefore, the process of
Covid-19 detection through PCR testing is time-consuming, and there is a 
shortage of these kits due to its high demand. Researchers around the world are
trying hard to seek out alternative ways to detect coronavirus. Radiation 
devices like X-rays and CT scans were offered as potential alternatives to the 
identification of COVID-19. CT-scan can be used to detect COVID-19 and is more 
sensitive to viral diagnosis than PCR

**Objectives**


*  To develop a model for image acquisition and enhancement. 

The uploaded image of the chest CT scan will be analyzed and prepared for 
segmentation. Various filters and tools are used for removing noises, change 
contrast, brightness and also other properties of the entire image or part of 
the image 


*  To develop a model for image segmentation. 

The image of the chest CT scan will be analyzed and objects in the image will be
separated. The aim of this objective is to separate the important parts from the
background of the image. 


*  To develop a model for recognizing the Covid-19 infected chest CT scan images using Machine Learning techniques. 

The AI model is developed with machine learning techniques to analyze and 
identify hidden patterns and relationships between the uploaded image and the 
trained data set of the AI model. 


*  To develop a mobile application. 

The aim of this objective is to develop the mobile application. The mobile 
application is used for taking photos of a chest CT scan and upload it to the 
cloud-based AI model for analyzing.

**IT18115130 Senevirathne K.D.A**
Image diagnosis is a vital problem in medicine. Now a day’s ongoing pandemic of 
Covid-19 has become the major infectious diseases among all other diseases. 
As we all know, Covid-19 is a fast-spreading viral disease. Researchers found 
that patients with Covid-19 have proved that they are mostly affected by lung 
diseases. Covid-19 is diagnosed using RT-PCR Testing, CT Scans and Chest X-Ray 
(CXR) images. But the problem is RT-PCR test takes at least more than 12 hours 
to get a result. Covid-19 patients should be identified and tracked as soon as 
possible, and it requires specific material equipment. In developing countries,
there is a lack of resources to do these tests. Even though methods that can 
generate faster results exist, these methods are too expensive for third-world 
countries like Sri Lanka.
Most people like to get their reports in minimum time. In this kind of a 
situation patients must wait for a long time, and it is stressful. If there is 
a proper and speed method that gives the result in very accurate way that will 
be helpful.
Chest X-ray images become the less cost and time-effective tool for take the 
decisions. Compared to other Chest X-ray methods, it is a lower-cost process, 
and anyone can easily access this method. In this global pandemic, frequent 
patients will need to be assessed in short periods by a few clinicians and very 
few resources.
Not only Covid-19 but also Pneumonia is an infectious disease that needs to be 
diagnosed at an early stage. With the introduction of imaging, the diagnosis of 
diseases using X-ray images of the chest has been accelerated. But it also 
requires a specialist and a qualified radiologist to read the chest X-ray image 
correctly. To this purpose, we are suggesting a joined method using image 
processing and Convolution Neural Network for automated detection of covid-19 
and pneumonia by using chest X-ray images.

**Objectives**
* Understanding correct objects and automatically process the data of that specific object and ready for the disease identification process. 

* Segment the captured chest x-ray image to identify the image. 

* Adding color filtering algorithm to the captured image 

* Organize processed Data for disease identification algorithms. 

* Developing an algorithm to analyze a sample of captured chest x-ray images to predict the disease. 

* Developing a method for classifying lung diseases

**IT18121698 Dias M.H.V**
Pneumonia, covid-19 are fatal diseases if it not detected on time. If it 
diagnoses at the right moment lots of lives will be saved.  Coronavirus disease 2019 (COVID-19)
is a respiratory tract infection caused by beta coronavirus SARS-CoV-2. Pneumonia
is an infection that inflames the air sacs in one or both lungs. So, both 
diseases cannot be taken as easy.  
When it comes to identifying these diseases there’s lack of facilities to detect
these diseases on time in developing countries. Great majority of these deaths
occur in resource-limited settings. There is no proper way than going to hospital
and do a PCR test to identify whether they are infected or not. In developing 
countries, there is a lack of resources to do these tests. So, the time taken to
a PCR test for a particular person is high. Sometimes it takes one week or more 
than that.
n these situations, patients must wait for long time and it is stressful. 
If there is a proper and speed method which gives the output in a very accurate 
way, that will be helpful. Then patients no longer wait for a long time and will
not be stressed.
When compared to the existing applications which have developed to identify 
covid-19, most of the applications only have the x-ray classification. The only 
output which we can get from those applications is whether we are positive or 
negative for pneumonia/covid-19. Those applications only consider x-ray screening. 
It does not give priority to the patient’s current health condition. Therefor the
accuracy level seems very low.
Patients who have undergone for surgeries, pregnancy conditions are major factors 
when compared to normal people who suffer from pneumonia and covid-19. They must
be specially considered when identifying the disease. They should give a high 
priority level and should be advised responsibly. But in the existing applications
there is no such priority given to those special people. It is another major 
problem that we have noticed during the literature survey. If this problem 
addressed properly it should helpful.
When a person suspected positive for pneumonia or covid-19 he/she should be 
advised about what they should do. Those patients should be directed for doctor
recommendation.  The existing applications do not have that facility. It is 
another major issue that we have monitored. Those applications only facilitate 
identifying and notify patients whether they are infected from pneumonia.

**Objectives**
Advice patient according to their severity level, give doctor recommendation 
if necessary is one of the most important section to be implement after the 
x-ray, CT scan classification. It is dominant to note that despite the fact 
that intelligent bots can offer identify the severity level, valuable facts 
and symptoms, they aren’t qualified and don’t have the authority to give an 
official treatment for diagnosis. Become the first point of contact before 
any human involvement is the main proposition behind these smart texting algorithms.


* Implement user friendly reliable communication method to interact with patient and gather information:  

To give an accurate result we have to get a clear understanding about the 
patient’s current health condition and past. In order to do that we suppose 
to implement intelligent bot to interact with the patient. This is a chunk 
of software that administer a discussions with patients via textual methods. 
chronic diseases, pregnancy, bad health habits, surgeries etc., are the basic 
information that we planned to ask from the patients. 


* To monitoring current health condition:  

To get an idea about what a patient is going through, the app asks them how the 
current condition of health and health history from a menu of descriptive words 
is. ex, if they are suffering from headache at the moment, they can rate that 
emotion/pain from “slightly” to “extremely.”  


* To give doctor recommendation/advice according to the severity level.  

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.  

**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.
