AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Radiologists

Showing 441 to 450 of 490 articles

Clear Filters

A Nationwide Web-Based Survey of Neuroradiologists' Perceptions of Artificial Intelligence Software for Neuro-Applications in Korea.

Korean journal of radiology
OBJECTIVE: We aimed to investigate current expectations and clinical adoption of artificial intelligence (AI) software among neuroradiologists in Korea.

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...

The role of artificial intelligence in clinical imaging and workflows.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Evidence-based medicine, outcomes management, and multidisciplinary systems are laying the foundation for radiology on the cusp of a new day. Environmental and operational forces coupled with technological advancements are redefining the veterinary r...

Artificial Intelligence-Based Identification of Normal Chest Radiographs: A Simulation Study in a Multicenter Health Screening Cohort.

Korean journal of radiology
OBJECTIVE: This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment.

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 ...

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...

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...