Formación en Radiodiagnóstico

Espacio editorial virtual

Formación en Radiodiagnóstico

Diagnostic accuracy of vision-language models on Japanese diagnostic radiology, nuclear medicine, and interventional radiology specialty board examinations

Radiol Med. 2024 Aug;129(8):1143-1155.

Oura T, Tatekawa H, Horiuchi D, Matsushita S, Takita H, Atsukawa N, Mitsuyama Y, Yoshida A, Murai K, Tanaka R, Shimono T, Yamamoto A, Miki Y, Ueda D.

Diagnostic performances of Claude 3 Opus and Claude 3.5 Sonnet from patient history and key images in Radiology’s “Diagnosis Please” cases

Jpn J Radiol 42, 1399–1402 (2024)

Kurokawa R, Ohizumi Y, Kanzawa J, Kurokawa M, Sonoda Y, Nakamura Y, Kiguchi T, Gonoi W, Abe O.

New trend in artificial intelligence‑based assistive technology for thoracic imaging

Radiol Med. 2023 Oct;128(10):1236-1249

Yanagawa M, Ito R, Nozaki T, Fujioka T, Yamada A, Fujita S, Kamagata K, Fushimi Y, Tsuboyama T, Matsui Y, Tatsugami F, Kawamura M, Ueda D, Fujima N, Nakaura T, Hirata K, Naganawa S.

Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs

Radiology: Artificial Intelligence 2024 6:5

Busch F, Bressem KK, Suwalski P, Hoffmann L, Niehues SM, Poddubnyy D, Makowsky MR, Aerts HJWL, Zhukov A, Adams LC.

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.