AI Medical Compendium Topic:
Radiology

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Clinical Comparable Corpus Describing the Same Subjects with Different Expressions.

Studies in health technology and informatics
Medical artificial intelligence (AI) systems need to learn to recognize synonyms or paraphrases describing the same anatomy, disease, treatment, etc. to better understand real-world clinical documents. Existing linguistic resources focus on variants ...

Causal Associations Among Diseases and Imaging Findings in Radiology Reports.

Studies in health technology and informatics
This study explored the ability to identify causal relationships between diseases and imaging findings from their co-occurrences in radiology reports. A natural language processing (NLP) system with negative-expression filtering detected positive men...

Scaling AI Projects for Radiology - Causes and Consequences.

Studies in health technology and informatics
Artificial intelligence (AI) for radiology has the potential to handle an ever-increasing volume of imaging examinations. However, the implementation of AI for clinical practice has not lived up to expectations. We suggest that a key problem with AI ...

A "Bumper-Car" Curriculum for Teaching Deep Learning to Radiology Residents.

Academic radiology
RATIONALE AND OBJECTIVES: Our goal was to create an artificial intelligence (AI) training curriculum for residents that taught them to create, train, evaluate and refine deep learning (DL) models. Hands-on training of models was emphasized and didact...

Quality use of artificial intelligence in medical imaging: What do radiologists need to know?

Journal of medical imaging and radiation oncology
The application of artificial intelligence, and in particular machine learning, to the practice of radiology, is already impacting the quality of imaging care. It will increasingly do so in the future. Radiologists need to be aware of factors that go...

Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration.

JNCI cancer spectrum
Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual...

Barriers to artificial intelligence implementation in radiology practice: What the radiologist needs to know.

Radiologia
Artificial Intelligence has the potential to disrupt the way clinical radiology is practiced globally. However, there are barriers that radiologists should be aware of prior to implementing Artificial Intelligence in daily practice. Barriers include ...

Artificial Intelligence in Radiology: an introduction to the most important concepts.

Radiologia
The interpretation of medical imaging tests is one of the main tasks that radiologists do. For years, it has been a challenge to teach computers to do this kind of cognitive task; the main objective of the field of computer vision is to overcome this...

Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?

Saudi medical journal
OBJECTIVES: To assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI.