The RSNA Pediatric Bone Age Machine Learning Challenge

PURPOSE: The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning (ML) and artificial intelligence (AI) in medical imaging, promote collaboration to catalyze AI model creation, and identify innovators in med...

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Dettagli Bibliografici
Pubblicato in:Radiology
Autori principali: Halabi, Safwan S., Prevedello, Luciano M., Kalpathy-Cramer, Jayashree, Mamonov, Artem B., Bilbily, Alexander, Cicero, Mark, Pan, Ian, Pereira, Lucas Araújo, Sousa, Rafael Teixeira, Abdala, Nitamar, Kitamura, Felipe Campos, Thodberg, Hans H., Chen, Leon, Shih, George, Andriole, Katherine, Kohli, Marc D., Erickson, Bradley J., Flanders, Adam E.
Natura: Artigo
Lingua:Inglês
Pubblicazione: Radiological Society of North America 2019
Soggetti:
Original Research
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6358027/
https://ncbi.nlm.nih.gov/pubmed/30480490
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/radiol.2018180736
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