Join the forefront of biomedical innovation and build a GPU-based deep learning model for multi-class classification of COVID-19, normal, and pneumonia cases. Outperform recent studies and make a valuable contribution to the research community by helping to accurately detect COVID-19 infections in their early stages, at an affordable cost.
Sign-up today at https://app.trustii.io
Contexte :
The COVID-19, also known as coronavirus disease 2019, is a viral illness caused by the SARS-CoV-2 strain of coronavirus. It originated in Wuhan, China in late 2019 and has since become a global pandemic, as declared by the WHO on March 11, 2020. Diagnosis of COVID-19 is typically done through RT-PCR testing, and chest X-rays can also be used to help with early detection of the disease.
Dataset :
It is a medical images directory structure containing Chest X-ray (CXR) Images of COVID19, NORMAL, PNEUMONIA. All images are preprocessed and resized to 256x256 in PNG format.
The dataset is a multi classification, it has three labels COVID, NORMAL and PNEUMONIA.
Competition :
Detect and classify COVID19 and Pneumonia from Chest X-Ray Images using Deep Learning methods.
If you are not familiar with images processing and deep learning you can take a look at few notebooks at Kaggle that handle chest x-ray images : https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia/code
Timeline :
The competition will open Thursday February 8th, at 8AM CET time. And it will be open until March 12nd.
Prize :
1st prize : 300 euros
2nd prize : 200 euros
Notebook GPU :
Trustii.io offers for free GPU based jupyter notebook, that you MUST use to build your model.
The notebook offers per user :
16 Gb GPU (Tesla T4)
4 vCPU
28 Gb RAM
100 Gb persistant storage
Trustii.io notebook comes with pre support of PyTorch, Tensorflow and Keras.
References :
Shastri, S., Kansal, I., Kumar, S. et al. CheXImageNet: a novel architecture for accurate classification of Covid-19 with chest x-ray digital images using deep convolutional neural networks. Health Technol. 12, 193204 (2022). https://doi.org/10.1007/s12553-021-00630-x
Kumar S, Shastri S, Mahajan S, et al. LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images. Int J Imaging Syst Technol. 2022;117. DOI: https://doi.org/10.1002/ima.22770