AI Medical Compendium Topic

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Radiology

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Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

The British journal of radiology
OBJECTIVES: Current state-of-the-art natural language processing (NLP) techniques use transformer deep-learning architectures, which depend on large training datasets. We hypothesized that traditional NLP techniques may outperform transformers for sm...

Opportunistic Screening: Scientific Expert Panel.

Radiology
Radiologic tests often contain rich imaging data not relevant to the clinical indication. Opportunistic screening refers to the practice of systematically leveraging these incidental imaging findings. Although opportunistic screening can apply to ima...

Current state of radiomics in pediatric neuro-oncology practice: a systematic review.

Pediatric radiology
BACKGROUND: Radiomics is the process of converting radiological images into high-dimensional data that may be used to create machine learning models capable of predicting clinical outcomes, such as disease progression, treatment response and survival...

Performance of ChatGPT on a Radiology Board-style Examination: Insights into Current Strengths and Limitations.

Radiology
Background ChatGPT is a powerful artificial intelligence large language model with great potential as a tool in medical practice and education, but its performance in radiology remains unclear. Purpose To assess the performance of ChatGPT on radiolog...

Revenue and Cost Analysis of a System Utilizing Natural Language Processing and a Nurse Coordinator for Radiology Follow-up Recommendations.

Current problems in diagnostic radiology
Radiology reports often contain recommendations for follow-up imaging, Provider adherence to these radiology recommendations can be incomplete, which may result in patient harm, lost revenue, or litigation. This study sought to perform a revenue asse...

Artificial intelligence in radiology - beyond the black box.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
BACKGROUND: Artificial intelligence is playing an increasingly important role in radiology. However, more and more often it is no longer possible to reconstruct decisions, especially in the case of new and powerful methods from the field of deep lear...

Sociodemographic Variables Reporting in Human Radiology Artificial Intelligence Research.

Journal of the American College of Radiology : JACR
PURPOSE: Artificial intelligence (AI) is rapidly reshaping how radiology is practiced. Its susceptibility to biases, however, is a primary concern as more AI algorithms become available for widespread use. So far, there has been limited evaluation of...

Clinical applications of artificial intelligence in radiology.

The British journal of radiology
The rapid growth of medical imaging has placed increasing demands on radiologists. In this scenario, artificial intelligence (AI) has become an attractive partner, one that may complement case interpretation and may aid in various non-interpretive as...