AI Medical Compendium Topic

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Radiology

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Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers.

BMC medical informatics and decision making
BACKGROUND: It is essential for radiologists to communicate actionable findings to the referring clinicians reliably. Natural language processing (NLP) has been shown to help identify free-text radiology reports including actionable findings. However...

Deep Learning-Based Natural Language Processing in Radiology: The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance.

Journal of medical systems
In radiology, natural language processing (NLP) allows the extraction of valuable information from radiology reports. It can be used for various downstream tasks such as quality improvement, epidemiological research, and monitoring guideline adherenc...

Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective.

Pediatric radiology
Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 certified AI products are available for chest radiography or chest CT. These AI products cover a wide ra...

Radiomics: a primer on high-throughput image phenotyping.

Abdominal radiology (New York)
Radiomics is a high-throughput approach to image phenotyping. It uses computer algorithms to extract and analyze a large number of quantitative features from radiological images. These radiomic features collectively describe unique patterns that can ...

Ethical impact of suboptimal referrals on delivery of care in radiology department.

Journal of medical ethics
The referral is the key source of information that enables radiologists and radiographers to provide quality services. However, the frequency of suboptimal referrals is widely reported. This research reviews the literature to illuminate the challenge...

Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group.

Radiography (London, England : 1995)
INTRODUCTION: Artificial intelligence (AI) has started to be increasingly adopted in medical imaging and radiotherapy clinical practice, however research, education and partnerships have not really caught up yet to facilitate a safe and effective tra...