AIMC Topic: Radiologists
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AI-powered Hyperrealism: Next Step in Cinematic Rendering?
Radiology
Jan 1, 2024
Background Recent advancements in artificial intelligence (AI)-powered image generation present opportunities to enhance three-dimensional medical images. Diffusion, an iterative denoising process, represents the standard of many of the current tools...
Revisiting the Trustworthiness of Saliency Methods in Radiology AI.
Radiology. Artificial intelligence
Jan 1, 2024
Purpose To determine whether saliency maps in radiology artificial intelligence (AI) are vulnerable to subtle perturbations of the input, which could lead to misleading interpretations, using prediction-saliency correlation (PSC) for evaluating the s...
How AI May Transform Musculoskeletal Imaging.
Radiology
Jan 1, 2024
While musculoskeletal imaging volumes are increasing, there is a relative shortage of subspecialized musculoskeletal radiologists to interpret the studies. Will artificial intelligence (AI) be the solution? For AI to be the solution, the wide impleme...
Radiologist's Guide to Evaluating Publications of Clinical Research on AI: How We Do It.
Radiology
Sep 1, 2023
Literacy in research studies of artificial intelligence (AI) has become an important skill for radiologists. It is required to make a proper assessment of the validity, reproducibility, and clinical applicability of AI studies. However, AI studies ar...
Clinical Impact of Deep Learning Reconstruction in MRI.
Radiographics : a review publication of the Radiological Society of North America, Inc
Jun 1, 2023
Deep learning has been recognized as a paradigm-shifting tool in radiology. Deep learning reconstruction (DLR) has recently emerged as a technology used in the image reconstruction process of MRI, which is an essential procedure in generating MR imag...
Artificial Intelligence in Breast Imaging: Challenges of Integration Into Clinical Practice.
Journal of breast imaging
May 22, 2023
Artificial intelligence (AI) in breast imaging is a rapidly developing field with promising results. Despite the large number of recent publications in this field, unanswered questions have led to limited implementation of AI into daily clinical prac...
Anticipating artificial intelligence in mammography screening: views of Swedish breast radiologists.
BMJ health & care informatics
May 1, 2023
OBJECTIVES: Artificial intelligence (AI) is increasingly tested and integrated into breast cancer screening. Still, there are unresolved issues regarding its possible ethical, social and legal impacts. Furthermore, the perspectives of different actor...
A Nationwide Web-Based Survey of Neuroradiologists' Perceptions of Artificial Intelligence Software for Neuro-Applications in Korea.
Korean journal of radiology
May 1, 2023
OBJECTIVE: We aimed to investigate current expectations and clinical adoption of artificial intelligence (AI) software among neuroradiologists in Korea.
DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology.
Clinical radiology
Feb 1, 2023
DECIDE-AI is a new, stage-specific reporting guideline for the early and live clinical evaluation of decision-support systems based on artificial intelligence (AI). It answers a need for more attention to the human factors influencing clinical AI per...
The time is now: making the case for a UK registry of deployment of radiology artificial intelligence applications.
Clinical radiology
Feb 1, 2023
Artificial intelligence (AI)-based healthcare applications (apps) are rapidly evolving, and radiology is a target specialty for their implementation. In this paper, we put the case for a national deployment registry to track the spread of AI apps int...
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