AI Medical Compendium Topic:
Radiology

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Chatbots and Large Language Models in Radiology: A Practical Primer for Clinical and Research Applications.

Radiology
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...

Revisiting the Trustworthiness of Saliency Methods in Radiology AI.

Radiology. Artificial intelligence
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...

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
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...

Early Experiences of Integrating an Artificial Intelligence-Based Diagnostic Decision Support System into Radiology Settings: A Qualitative Study.

Studies in health technology and informatics
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 organizational practic...

FDA-cleared artificial intelligence and machine learning-based medical devices and their 510(k) predicate networks.

The Lancet. Digital health
The US Food and Drug Administration is clearing an increasing number of artificial intelligence and machine learning (AI/ML)-based medical devices through the 510(k) pathway. This pathway allows clearance if the device is substantially equivalent to ...

Quantifying Uncertainty in Deep Learning of Radiologic Images.

Radiology
In recent years, deep learning (DL) has shown impressive performance in radiologic image analysis. However, for a DL model to be useful in a real-world setting, its confidence in a prediction must also be known. Each DL model's output has an estimate...