AlexSWong/COVID-Net
Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global multi-disciplinary team of researchers, developers, and clinicians have made publicly available a suite of tailored deep neural network models for tackling different challenges ranging from screening to risk stratification to treatment planning for patients with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, we have made available fully curated, open access benchmark datasets comprised of some of the largest, most diverse patient cohorts from around the world.
This initiative provides AI models and large datasets to help healthcare workers detect and manage respiratory illnesses and cancer. It takes medical images like X-rays, CT scans, or ultrasound, along with clinical data, and outputs predictions for screening, risk assessment, or disease progression. Medical practitioners and researchers can use this to aid in diagnosis and treatment planning.
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Use this if you are a clinician or researcher needing advanced AI tools to help with early detection, risk stratification, and treatment planning for COVID-19, tuberculosis, pulmonary fibrosis, or various cancers.
Not ideal if you are looking for a fully integrated, certified diagnostic tool for immediate patient care without further validation or integration into existing clinical workflows.
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Dec 19, 2023
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