Lataa...

Improving Automated Pediatric Bone Age Estimation Using Ensembles of Models from the 2017 RSNA Machine Learning Challenge

PURPOSE: To investigate improvements in performance for automatic bone age estimation that can be gained through model ensembling. MATERIALS AND METHODS: A total of 48 submissions from the 2017 RSNA Pediatric Bone Age Machine Learning Challenge were used. Participants were provided with 12 611 pedia...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Julkaisussa:Radiol Artif Intell
Päätekijät: Pan, Ian, Thodberg, Hans Henrik, Halabi, Safwan S., Kalpathy-Cramer, Jayashree, Larson, David B.
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Radiological Society of North America 2019
Aiheet:
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC6884060/
https://ncbi.nlm.nih.gov/pubmed/32090207
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2019190053
Tagit: Lisää tagi
Ei tageja, Lisää ensimmäinen tagi!