Tackles Labs
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Date
2019
Authors
Abu-Eideh, Ayman
Habiba, Zaid
Journal Title
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Abstract
Chest radiography is the most common imaging globally , and it’s used to diagnose
diseases and conditions affecting the chest and it’s nearby structure. One of the
infirmity used to be diagnosed is pneumonia . Pneumonia is an infection of the
lungs which is caused by bacteria or viruses. It affects approximately 450 million
people globally (7% of the population) and results in about four million deaths
per year according to world health organization ( WHO ) . Early detection of
pneumonia can help doctors to treat patients as soon as possible ,also the detection
of pneumonia requires a radiologist with a good experience , but in many places in
the world there isn’t experienced radiologists . This project will focus on building
an application that detects chest pneumonia by building a machine learning model
based on dataset provided by NIH and labeled by experienced radiologists which
contains more than 20000 X-ray photos of pneumonia and normal chests , to detect
if the patient suffer from pneumonia or not. The application is WEP application
which will be build in React framework .The application will provide the following
features .At first it will detect pneumonia disease from X-ray photos . secondly it’ll
provide 3 types of users , X-ray labs ,doctors and patients. The labs will provide
the patient’s chest X-ray photo and send it to his doctor and to the patient himself.
Also the patient can send it to other doctor to diagnose photos , the doctor will
diagnose X-ray photo and provide the patient with a good treatments , also the
patient will have a medical history which will be uploaded by his doctors and
these histories will be seen by his doctor to him in diagnosing process. The final
feature is the website will provide a hub of models that makes any developer add
his medical model that helps the doctors to diagnose the illness of the patient.