AIMC Topic: Radiography
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Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA.
Radiology. Artificial intelligence
Jan 1, 2024
Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing ...
Chatbots and Large Language Models in Radiology: A Practical Primer for Clinical and Research Applications.
Radiology
Jan 1, 2024
Although chatbots have existed for decades, the emergence of transformer-based large language models (LLMs) has captivated the world through the most recent wave of artificial intelligence chatbots, including ChatGPT. Transformers are a type of neura...
Identification of L5 vertebra on lumbar spine radiographs using deep learning.
The Journal of international medical research
Jan 1, 2024
OBJECTIVE: Deep learning is an advanced machine-learning approach that is used in several medical fields. Here, we developed a deep learning model using an object detection algorithm to identify the L5 vertebra on anteroposterior lumbar spine radiogr...
Present and Future Innovations in AI and Cardiac MRI.
Radiology
Jan 1, 2024
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and long acquisition protocols limit the specialty and restrain its impact on ...
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...
Challenges of using artificial intelligence to detect valvular heart disease from chest radiography.
The Lancet. Digital health
Jan 1, 2024
Challenges of using artificial intelligence to detect valvular heart disease from chest radiography - Authors' reply.
The Lancet. Digital health
Jan 1, 2024
Early experiences of integrating an artificial intelligence-based diagnostic decision support system into radiology settings: a qualitative study.
Journal of the American Medical Informatics Association : JAMIA
Dec 22, 2023
OBJECTIVES: Artificial intelligence (AI)-based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizati...
[Automated cephalometric landmark identification and location based on convolutional neural network].
Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
Dec 9, 2023
To develop an automated landmark location system applicable to the case of landmark missing. Four and eighty-one lateral cephalograms, which contained 240 males and 241 females, with an average age of (24.5±5.6) years, taken from January 2015 to Ja...
Coarse Race and Ethnicity Labels Mask Granular Underdiagnosis Disparities in Deep Learning Models for Chest Radiograph Diagnosis.
Radiology
Nov 1, 2023
See also the editorial by Nikolic in this issue.
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