Detection of COVID-19 from Chest X-ray
by Yash Bajaj
An attempt- Detection of COVID-19 presence from Chest X-ray scans using CNN.
License: MIT License
Model stats and performance
Inference time in seconds per sample.
Performance data is not available.
An attempt- Detection of COVID-19 presence from Chest X-ray scans using CNN
Coronavirus disease 2019 (COVID-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2. The disease first originated in December 2919 from Wuhan, China and since then it has spread globally across the world affecting more than 200 countries. The impact is such that the World Health Organization(WHO) has declared the ongoing pandemic of COVID-19 a Public Health Emergency of International Concern
The 2019 novel coronavirus (COVID-19) presents several unique features. While the diagnosis is confirmed using polymerase chain reaction (PCR), infected patients with pneumonia may present on chest X-ray and computed tomography (CT) images with a pattern that is only moderately characteristic for the human eye Ng, 2020. COVID-19’s rate of transmission depends on our capacity to reliably identify infected patients with a low rate of false negatives. In addition, a low rate of false positives is required to avoid further increasing the burden on the healthcare system by unnecessarily exposing patients to quarantine if that is not required. Along with proper infection control, it is evident that timely detection of the disease would enable the implementation of all the supportive care required by patients affected by COVID-19.
Note: Please do not claim the diagnostic performance of a model without a clinical study! This is not a Kaggle competition dataset.
Dataset is taken from the below reference
To Run the code
To get all the requirements and dependencies installed run the command For GPU - pip install -r gpu_requirements.txt For CPU - pip install -r cpu_requirements.txt
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Computer Engineer | Machine Learning Enthusiastic | Data Science | Salesforce
Experienced Salesforce Developer and Machine Learning with a demonstrated history of working in the information technology and services industry. Skilled in Java, Android Development, HTML, and Internet of Things. Strong information technology professional with a Bachelor of Technology - BTech focused in Computer Engineering from Uka Tarsadia University .
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