Results 41 to 50 of about 167,942 (343)

Cross-sectional study of the provision of interventional oncology services in the UK [PDF]

, 2017
Objective: To map out the current provision of interventional oncology (IO) services in the UK. Design: Cross-sectional multicentre study. Setting: All National Health Service (NHS) trusts in England and Scottish, Welsh and Northern Ireland health ...
Alcorn, Des J., Atiiga, Peter, Breen, David J., Haslam, Philip J., Illing, Rowland, Kay, David, McCafferty, Ian J., Railton, Nicholas, Wah, Tze Min, Zhong, Jim   +9 more
core   +1 more source

Professionals’ responses to the introduction of AI innovations in radiology and their implications for future adoption: a qualitative study

BMC Health Services Research, 2021
Background Artificial Intelligence (AI) innovations in radiology offer a potential solution to the increasing demand for imaging tests and the ongoing workforce crisis. Crucial to their adoption is the involvement of different professional groups, namely
Yaru Chen, C. Stavropoulou, Radhika Narasinkan, A. Baker, H. Scarbrough   +4 more
semanticscholar   +1 more source

PERCEPTION OF RADIOLOGISTS ABOUT DIAGNOSTIC ERRORS IN RADIOLOGY IN YEMEN

Yemeni Journal for Medical Sciences, 2014
Background: Errors of diagnosis in Radiology are common affecting patient’s care and management. Several types of radiological errors such as misperception, miscommunication, and procedure misconduct have been reported highlighting the important of ...
Hameed M Aklan
doaj   +3 more sources

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

Japanese Journal of Radiology
The advent of Deep Learning (DL) has significantly propelled the field of diagnostic radiology forward by enhancing image analysis and interpretation. The introduction of the Transformer architecture, followed by the development of Large Language Models (
Takeshi Nakaura, Rintaro Ito, Daiju Ueda, Taiki Nozaki, Yasutaka Fushimi, Yusuke Matsui, Masahiro Yanagawa, Akira Yamada, T. Tsuboyama, N. Fujima, F. Tatsugami, Kenji Hirata, S. Fujita, K. Kamagata, Tomoyuki Fujioka, M. Kawamura, Shinji Naganawa   +16 more
semanticscholar   +1 more source

ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists’ training

European Radiology, 2020
Objectives This study aims to define consensus-based criteria for acquiring and reporting prostate MRI and establishing prerequisites for image quality.
M. de Rooij, B. Israël, M. Tummers, H. Ahmed, T. Barrett, F. Giganti, B. Hamm, V. Løgager, A. Padhani, V. Panebianco, P. Puech, J. Richenberg, O. Rouvière, G. Salomon, I. Schoots, J. Veltman, G. Villeirs, J. Walz, J. Barentsz   +18 more
semanticscholar   +1 more source

HISTORIA DEL ULTRASONIDO: EL CASO CHILENO

Revista Chilena de Radiología
Tras su descripción hace largo tiempo, el ultrasonido derivó hacia aplicaciones prácticas, entre ellas el diagnóstico médico. Las innovaciones tecnológicas continuas, incluyendo el Doppler, aumentaron tanto el rango de órganos interrogados como los ...
T Ortega, Solange Seguel B
doaj   +1 more source

ChatGPT’s diagnostic performance based on textual vs. visual information compared to radiologists’ diagnostic performance in musculoskeletal radiology

European Radiology
To compare the diagnostic accuracy of Generative Pre-trained Transformer (GPT)-4-based ChatGPT, GPT-4 with vision (GPT-4V) based ChatGPT, and radiologists in musculoskeletal radiology. We included 106 “Test Yourself” cases from Skeletal Radiology between
Daisuke Horiuchi, Hiroyuki Tatekawa, Tatsushi Oura, T. Shimono, Shannon L. Walston, H. Takita, Shunichi Matsushita, Yasuhito Mitsuyama, Yukio Miki, Daiju Ueda   +9 more
semanticscholar   +1 more source

Impact of the rise of artificial intelligence in radiology: What do radiologists think?

Diagnostic and Interventional Imaging, 2019
PURPOSE The purpose of this study was to assess the perception, knowledge, wishes and expectations of a sample of French radiologists towards the rise of artificial intelligence (AI) in radiology.
Q. Waymel, S. Badr, X. Demondion, A. Cotten, Thibaut Jacques   +4 more
semanticscholar   +1 more source

Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points

Heliyon, 2023
Background: The integration of Artificial Intelligence (AI)-based technologies in medicine is advancing rapidly especially in the field of radiology. This however, is at a slow pace in Africa, hence, this study to evaluate the perspectives of Ghanaian ...
Emmanuel Kobina Mesi Edzie, Klenam Dzefi-Tettey, Abdul Raman Asemah, Edmund Kwakye Brakohiapa, Samuel Asiamah, Frank Quarshie, Adu Tutu Amankwa, Amrit Raj, Obed Nimo, Evans Boadi, Joshua Mensah Kpobi, Richard Ato Edzie, Bernard Osei, Veronica Turkson, Henry Kusodzi   +14 more
doaj   +1 more source

Comparative analysis of GPT-4-based ChatGPT’s diagnostic performance with radiologists using real-world radiology reports of brain tumors

European Radiology
Large language models like GPT-4 have demonstrated potential for diagnosis in radiology. Previous studies investigating this potential primarily utilized quizzes from academic journals.
Yasuhito Mitsuyama, Hiroyuki Tatekawa, H. Takita, Fumi Sasaki, Akane Tashiro, Satoshi Oue, Shannon L. Walston, Yuta Nonomiya, Ayumi K. Shintani, Yukio Miki, Daiju Ueda   +10 more
semanticscholar   +1 more source