AIMC Topic: Radiology

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Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase.

Abdominal radiology (New York) Sep 16, 2020
PURPOSE: To evaluate the performance of trained technologists vis-à-vis radiologists for volumetric pancreas segmentation and to assess the impact of supplementary training on their performance.
Humans Artificial Intelligence Tomography, X-Ray Computed Reproducibility of Results COVID-19 Retrospective Studies Pancreas Clinical Competence Image Processing, Computer-Assisted Radiology Datasets as Topic
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Training Radiology Residents, Bloom Style.

Academic radiology Sep 10, 2020
Bloom's Taxonomy, an integral component of learning theory since its inception, describes cognitive skill levels in increasing complexity (Remember, Understand, Apply, Analyze, Evaluate, and Create). Considering Bloom's Taxonomy when writing learning...
Thinking Educational Measurement Humans Radiology Artificial Intelligence Learning
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Sharing and Selling Images: Ethical and Regulatory Considerations for Radiologists.

Journal of the American College of Radiology : JACR Sep 2, 2020
Opportunities to share or sell images are common in radiology. But because these images typically originate as protected health information, their use admits a host of ethical and regulatory considerations. This article discusses four scenarios that ...
Humans Radiologists Information Dissemination Attitude Artificial Intelligence Radiology
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Patient Safety: Considerations for Artificial Intelligence Implementation in Radiology.

Journal of the American College of Radiology : JACR Aug 27, 2020
Radiography Humans Radiology Artificial Intelligence
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Making Your AI Smarter: Continuous Learning Artificial Intelligence for Radiology.

Radiology Aug 25, 2020
Radiology Humans Learning Artificial Intelligence Radiologists Radiography
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Continuous Learning AI in Radiology: Implementation Principles and Early Applications.

Radiology Aug 25, 2020
Artificial intelligence (AI) is becoming increasingly present in radiology and health care. This expansion is driven by the principal AI strengths: automation, accuracy, and objectivity. However, as radiology AI matures to become fully integrated int...
Humans Artificial Intelligence Big Data Radiology
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Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing.

Journal of digital imaging Aug 19, 2020
The ideal radiology report reduces diagnostic uncertainty, while avoiding ambiguity whenever possible. The purpose of this study was to characterize the use of uncertainty terms in radiology reports at a single institution and compare the use of thes...
Radiology Information Systems Uncertainty Radiology Research Report Humans Natural Language Processing
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A brief introduction to concepts and applications of artificial intelligence in dental imaging.

Oral radiology Aug 16, 2020
This report aims to summarize the fundamental concepts of Artificial Intelligence (AI), and to provide a non-exhaustive overview of AI applications in dental imaging, comprising diagnostics, forensics, image processing and image reconstruction. AI ha...
Artificial Intelligence Machine Learning Algorithms Image Processing, Computer-Assisted Radiology
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Challenges and solutions for introducing artificial intelligence (AI) in daily clinical workflow.

European radiology Aug 14, 2020
Radiology Workflow Humans Artificial Intelligence
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Thyroid Ultrasound Reports: Will the Thyroid Imaging, Reporting, and Data System Improve Natural Language Processing Capture of Critical Thyroid Nodule Features?

The Journal of surgical research Aug 13, 2020
BACKGROUND: Critical thyroid nodule features are contained in unstructured ultrasound (US) reports. The Thyroid Imaging, Reporting, and Data System (TI-RADS) uses five key features to risk stratify nodules and recommend appropriate intervention. This...
Hospitals, Community Societies, Medical Practice Guidelines as Topic Data Systems Ultrasonography Radiology Thyroid Nodule Academic Medical Centers Retrospective Studies Image Processing, Computer-Assisted Thyroid Gland Humans Natural Language Processing
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