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Radiologists

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Assessment of an artificial intelligence aid for the detection of appendicular skeletal fractures in children and young adults by senior and junior radiologists.

Pediatric radiology
BACKGROUND: As the number of conventional radiographic examinations in pediatric emergency departments increases, so, too, does the number of reading errors by radiologists.

Transfer learning in diagnosis of maxillary sinusitis using panoramic radiography and conventional radiography.

Oral radiology
OBJECTIVES: To clarify the performance of transfer learning with a small number of Waters' images at institution B in diagnosing maxillary sinusitis, based on a source model trained with a large number of panoramic radiographs at institution A.

Utility of the deep learning technique for the diagnosis of orbital invasion on CT in patients with a nasal or sinonasal tumor.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: In nasal or sinonasal tumors, orbital invasion beyond periorbita by the tumor is one of the important criteria in the selection of the surgical procedure. We investigated the usefulness of the convolutional neural network (CNN)-based deep...

Act Like a Radiologist: Towards Reliable Multi-View Correspondence Reasoning for Mammogram Mass Detection.

IEEE transactions on pattern analysis and machine intelligence
Mammogram mass detection is crucial for diagnosing and preventing the breast cancers in clinical practice. The complementary effect of multi-view mammogram images provides valuable information about the breast anatomical prior structure and is of gre...

Artificial Intelligence for the Analysis of Workload-Related Changes in Radiologists' Gaze Patterns.

IEEE journal of biomedical and health informatics
Around 60-80% of radiological errors are attributed to overlooked abnormalities, the rate of which increases at the end of work shifts. In this study, we run an experiment to investigate if artificial intelligence (AI) can assist in detecting radiolo...

Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists.

Radiology
Background The World Health Organization (WHO) recommends chest radiography to facilitate tuberculosis (TB) screening. However, chest radiograph interpretation expertise remains limited in many regions. Purpose To develop a deep learning system (DLS)...

Natural Language Processing in Radiology: Update on Clinical Applications.

Journal of the American College of Radiology : JACR
Radiological reports are a valuable source of information used to guide clinical care and support research. Organizing and managing this content, however, frequently requires several manual curations because of the more common unstructured nature of ...

Patient communication in radiology: Moving up the agenda.

European journal of radiology
Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients can be challenging in the setting of busy radiology departments where there is a fo...