AIMC Topic: Quality Improvement
Clear Filters Showing 171 to 180 of 194 articles
Artificial Intelligence in Quality Improvement: Reviewing Uses of Artificial Intelligence in Noninterpretative Processes from Clinical Decision Support to Education and Feedback.
Journal of the American College of Radiology : JACR
Nov 1, 2020
The radiology workflow can be segmented into three large groups: pre-interpretative processes, interpretation, and postinterpretative processes. Each stage of this workflow represents quality improvement opportunities for artificial intelligence and ...
A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2020
OBJECTIVE: The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical information systems. In this article, we introduce a novel transformation-based auditing method that leverage...
Portable Automated Surveillance of Surgical Site Infections Using Natural Language Processing: Development and Validation.
Annals of surgery
Oct 1, 2020
OBJECTIVES: We present the development and validation of a portable NLP approach for automated surveillance of SSIs.
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
The journal of trauma and acute care surgery
May 1, 2020
BACKGROUND: Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize...
Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records.
Rheumatology (Oxford, England)
May 1, 2020
OBJECTIVES: To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Clas...
Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?
Prevention science : the official journal of the Society for Prevention Research
Feb 1, 2020
The cost-effectiveness of targeted delinquency prevention programs for children depends on the accuracy of the screening process. Screening accuracy is often poor, resulting in wasted resources and missed opportunities to avert negative outcomes. Thi...
Possibility of Deep Learning in Medical Imaging Focusing Improvement of Computed Tomography Image Quality.
Journal of computer assisted tomography
Jan 1, 2020
Deep learning (DL), part of a broader family of machine learning methods, is based on learning data representations rather than task-specific algorithms. Deep learning can be used to improve the image quality of clinical scans with image noise reduct...
A Business Case for Artificial Intelligence Tools: The Currency of Improved Quality and Reduced Cost.
Journal of the American College of Radiology : JACR
Sep 1, 2019
For data science tools to mature and become integrated into routine clinical practice, they must add value to patient care by improving quality without increasing cost, by reducing cost without changing quality, or by both reducing cost and improving...
Artificial Intelligence and Clinical Decision Support for Radiologists and Referring Providers.
Journal of the American College of Radiology : JACR
Sep 1, 2019
Recent advances in artificial intelligence (AI) are providing an opportunity to enhance existing clinical decision support (CDS) tools to improve patient safety and drive value-based imaging. We discuss the advantages and potential applications that ...
Big Data and Radiology Research.
Journal of the American College of Radiology : JACR
Sep 1, 2019
Our understanding of human health may be significantly enhanced in the near future because of the unprecedented volume of digitized health care data and the availability of artificial intelligence to mine these data for correlations that could drive ...
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