AIMC Topic: Radiology

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Medical Student Perspectives on the Impact of Artificial Intelligence on the Practice of Medicine.

Current problems in diagnostic radiology
INTRODUCTION: Concerns about radiologists being replaced by artificial intelligence (AI) from the lay media could have a negative impact on medical students' perceptions of radiology as a viable specialty. The purpose of this study was to evaluate Un...

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning.

Journal of biomedical informatics
Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Suc...

Artificial intelligence from A to Z: From neural network to legal framework.

European journal of radiology
Artificial intelligence (AI) will continue to cause substantial changes within the field of radiology, and it will become increasingly important for clinicians to be familiar with several concepts behind AI algorithms in order to effectively guide th...

Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors.

European radiology
OBJECTIVE: The objective was to identify barriers and facilitators to the implementation of artificial intelligence (AI) applications in clinical radiology in The Netherlands.

Deep learning for dermatologists: Part II. Current applications.

Journal of the American Academy of Dermatology
Because of a convergence of the availability of large data sets, graphics-specific computer hardware, and important theoretical advancements, artificial intelligence has recently contributed to dramatic progress in medicine. One type of artificial in...

Deep learning in generating radiology reports: A survey.

Artificial intelligence in medicine
Substantial progress has been made towards implementing automated radiology reporting models based on deep learning (DL). This is due to the introduction of large medical text/image datasets. Generating radiology coherent paragraphs that do more than...

Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry.

Academic radiology
OBJECTIVES: We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work.

Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?

European radiology
Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integration of the versatile diagnostic information, e.g., from anamnesis, imaging, histopathology, and c...

Understanding artificial intelligence based radiology studies: What is overfitting?

Clinical imaging
Artificial intelligence (AI) is a broad umbrella term used to encompass a wide variety of subfields dedicated to creating algorithms to perform tasks that mimic human intelligence. As AI development grows closer to clinical integration, radiologists ...