Formación en Radiodiagnóstico

Espacio editorial virtual

Formación en Radiodiagnóstico

Canadian Association of Radiologists Statement on Environmental Sustainability in Medical Imaging

Can Assoc Radiol J. 2024 Jul 30:8465371241260013

Kate Hanneman, Andrew Szava-Kovats, Brent Burbridge, David Leswick, Brandon Nadeau, Omar Islam, Emil J. Y. Lee, Alison Harris, Candyce Hamel, and Maura J. Brown.

The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI.

Jpn J Radiol 42, 685–696 (2024).

Nakaura, T., Ito, R., Ueda, D. et al.

Clinical trials for evidence‑based radiology: to randomize or not to randomize? This is the question

La radiologia medica (2024) 129:80–82

Anna Colarieti, Francesco Sardanelli

Dual-Energy CT: New Horizon in Medical Imaging

Korean J Radiol 2017;18(4):555-569

Goo HW, Goo JM.

Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels

Korean J Radiol. 2023 Nov;24(11):1151-1163.

Kim PH, Yoon HM, Kim JR, Hwang JY, Choi JH, Hwang J, Lee J, Sung J, Jung KH, Bae B, Jung AY, Cho YA, Shim WH, Bak B, Lee JS. Bone Age

Comités

Áreas de conocimiento

Radiología Pediátrica

Radiología Musculoesquelética

Radiología Intervencionista

Radiología de Urgencias

Radiología de la Mama

Radiología de Abdomen

Radiología Cardiotorácica

Neurorradiología

Gestión y Calidad en Radiodiagnóstico

Formación en Radiodiagnóstico

Área de Ultrasonidos

Sociedades participantes

SEUS

SERVEI

SERPE

SERME

SERAU

SENR

SEICAT

SEGECA

SEDIM

SEDIA

FORA

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