AI Medical Compendium Topic

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Radiology

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Social Asymmetry, Artificial Intelligence and the Medical Imaging Landscape.

Seminars in nuclear medicine
Social and health care equity and justice should be prioritized by the mantra of medicine, first do no harm. Despite highly motivated national and global health strategies, there remains significant health care inequity. Intrinsic and extrinsic facto...

The role of artificial intelligence in paediatric cardiovascular magnetic resonance imaging.

Pediatric radiology
Artificial intelligence (AI) offers the potential to change many aspects of paediatric cardiac imaging. At present, there are only a few clinically validated examples of AI applications in this field. This review focuses on the use of AI in paediatri...

Impact of Concurrent Use of Artificial Intelligence Tools on Radiologists Reading Time: A Prospective Feasibility Study.

Academic radiology
RATIONAL AND OBJECTIVES: This study investigated how an AI tool impacted radiologists reading time for non-contrast chest CT exams.

Automatic Forecasting of Radiology Examination Volume Trends for Optimal Resource Planning and Allocation.

Journal of digital imaging
The aim of the study was to evaluate the performance of the Prophet forecasting procedure, part of the Facebook open-source Artificial Intelligence portfolio, for forecasting variations in radiological examination volumes. Daily CT and MRI examinatio...

Biomedical Ontologies to Guide AI Development in Radiology.

Journal of digital imaging
The advent of deep learning has engendered renewed and rapidly growing interest in artificial intelligence (AI) in radiology to analyze images, manipulate textual reports, and plan interventions. Applications of deep learning and other AI approaches ...

An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research.

Korean journal of radiology
Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by s...

AI Integration in the Clinical Workflow.

Journal of digital imaging
Machine learning and artificial intelligence (AI) algorithms hold significant promise for addressing important clinical needs when applied to medical imaging; however, integration of algorithms into a radiology department is challenging. Vended algor...

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after r...

The augmented radiologist: artificial intelligence in the practice of radiology.

Pediatric radiology
In medicine, particularly in radiology, there are great expectations in artificial intelligence (AI), which can "see" more than human radiologists in regard to, for example, tumor size, shape, morphology, texture and kinetics - thus enabling better c...

Do People Favor Artificial Intelligence Over Physicians? A Survey Among the General Population and Their View on Artificial Intelligence in Medicine.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: To investigate the general population's view on artificial intelligence (AI) in medicine with specific emphasis on 3 areas that have experienced major progress in AI research in the past few years, namely radiology, robotic surgery, and d...