Can artificial intelligence pass the Fellowship of the Royal College of Radiologists examination? Multi-reader diagnostic accuracy study

OBJECTIVE: To determine whether an artificial intelligence candidate could pass the rapid (radiographic) reporting component of the Fellowship of the Royal College of Radiologists (FRCR) examination. DESIGN: Prospective multi-reader diagnostic accuracy study. SETTING: United Kingdom. PARTICIPANTS: O...

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Detalles Bibliográficos
Autores principales: Shelmerdine, Susan Cheng, Martin, Helena, Shirodkar, Kapil, Shamshuddin, Sameer, Weir-McCall, Jonathan Richard, AlQarooni, Sayed Hashim, Alias, Sajay, Aryasomayajula, Saraswati Samyukta, Azzi, Caline, Ba Hashwan, Awadh Ahmed Taiseir, Boon-Itt, Anintitha, Butt, Momana Tariq, Chang, Liisa, Crowe, Victoria, Elsaidy, Mahmoud Mohamed, Gonegandla, Aejaz Ahmed, Hammond, Abeeku Afedzi, Jantre, Mansi, Karthikeyan, Kavya Moonjelil, Koo, Sharon, McGlade, Sophie, Mehta, Aprajita, Mundhada, Preeti, Nayel, Marwa, Ngu, Wee Ping, Norman, Ryan, Odeh, Amina, Perumala, Dileep Kumar, Roy Choudhury, Shayeri, Stephen Maria Lourdam, Sarath Babu, Virupakshappa, Anil Kumar Geetha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group Ltd. 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768816/
https://www.ncbi.nlm.nih.gov/pubmed/36543352
http://dx.doi.org/10.1136/bmj-2022-072826

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768816/
https://www.ncbi.nlm.nih.gov/pubmed/36543352
http://dx.doi.org/10.1136/bmj-2022-072826

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