Quantitative Analysis of Uncertainty in Medical Reporting: Creating a Standardized and Objective Methodology.
Uncertainty in text-based medical reports has long been recognized as problematic, frequently resulting in misunderstanding and miscommunication. One strategy for addressing the negative clinical ramifications of report uncertainty would be the creation of a standardized methodology for characterizing and quantifying uncertainty language, which could provide both the report author and reader with context related to the perceived level of diagnostic confidence and accuracy. A number of computerized strategies could be employed in the creation of this analysis including string search, natural language processing and understanding, histogram analysis, topic modeling, and machine learning. The derived uncertainty data offers the potential to objectively analyze report uncertainty in real time and correlate with outcomes analysis for the purpose of context and user-specific decision support at the point of care, where intervention would have the greatest clinical impact.
Published In/Presented At
Reiner B. I. (2018). Quantitative Analysis of Uncertainty in Medical Reporting: Creating a Standardized and Objective Methodology. Journal of digital imaging, 31(2), 145–149. https://doi.org/10.1007/s10278-017-0041-z
Diagnosis | Medicine and Health Sciences | Other Analytical, Diagnostic and Therapeutic Techniques and Equipment | Radiology
Department of Radiology and Diagnostic Medical Imaging