AIMC Topic: Artificial Intelligence

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PyVisualFields: A Python Package for Visual Field Analysis.

Translational vision science & technology
PURPOSE: Artificial intelligence (AI) methods are changing all areas of research and have a variety of capabilities of analysis in ophthalmology, specifically in visual fields (VFs) to detect or predict vision loss progression. Whereas most of the AI...

Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs.

Korean journal of radiology
OBJECTIVE: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the conc...

The top 100 most cited articles on artificial intelligence in radiology: a bibliometric analysis.

Clinical radiology
AIM: To identify the most influential publications relating to artificial intelligence (AI) in radiology in order to identify current trends in the literature and to highlight areas requiring further research.

Utilisation of deep learning for COVID-19 diagnosis.

Clinical radiology
The COVID-19 pandemic that began in 2019 has resulted in millions of deaths worldwide. Over this period, the economic and healthcare consequences of COVID-19 infection in survivors of acute COVID-19 infection have become apparent. During the course o...

DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology.

Clinical radiology
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
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...