While uncertainty is ubiquitous in medical practice, minimal work to date has been performed to analyze the cause and effect relationship between uncertainty and patient outcomes. In medical imaging practice, uncertainty in the radiology report has been well documented to be a source of clinician dissatisfaction. Before one can effectively create intervention strategies aimed at reducing uncertainty, it must first be better understood through context- and user-specific analysis. One strategy for accomplishing this task is to characterize the source of uncertainty and create user-specific uncertainty profiles which take into account a number of provider-specific variables which may contribute to report uncertainty. The resulting data can in turn be used to create real-time report uncertainty metrics aimed at providing uncertainty analytics at the point of care, for the combined purposes of decision support, improved communication, and enhanced clinical/economic outcomes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113141 | PMC |
http://dx.doi.org/10.1007/s10278-018-0057-z | DOI Listing |
J Med Internet Res
January 2025
Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States.
Background: Clinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. Yet, little is known about the effects on human cognition as a result of interacting with such types of AI advice.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Division of General Internal Medicine, Department of Medicine, Institute for Artificial Intelligence in Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Updates Surg
January 2025
Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Anal Bioanal Chem
January 2025
TUM School of Natural Sciences, Chair of Analytical Chemistry and Water Chemistry, Technical University of Munich, Lichtenbergstraße 4, 85748, Garching, Germany.
Compound-specific isotope analysis (CSIA) is a potent method for illustrating the in situ degradation of aquatic contaminants. However, its application to surface and groundwater is hindered by low contaminant concentrations, typically in the nanogram-per-litre range, requiring the processing of large water volumes. Polar organic chemical integrative samplers (POCIS) have shown promising results when combined with CSIA, yet their extended deployment time to accumulate sufficient analyte mass remains a major limitation.
View Article and Find Full Text PDFGlob Chang Biol
February 2025
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China.
There are still large uncertainties on the relationships between microbial carbon use efficiency and soil organic carbon across (1) different carbon use efficiency estimation methods, (2) various temporal, spatial and biological scales, and (3) multiple climate change scenarios. These uncertainties call for further efforts to re-examine the relationships between carbon use efficiency and soil organic carbon to better represent microbial processes in the current modelling frameworks.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!