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Uncertainty in Measurement: Reading Instruments

Uncertainty in Measurement: Reading Instruments

Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...

Uncertainty: Overview

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.

Propagation of Uncertainty from Random Error

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

Propagation of Uncertainty from Systematic Error

Propagation of Uncertainty from Systematic Error

The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...

Uncertainty: Confidence Intervals

Uncertainty: Confidence Intervals

The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...

Uncertainty in Measurement: Accuracy and Precision

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing.

Andrew L Callen¹, Sara M Dupont², Adi Price³

¹Department of Radiology, University of Colorado Anschutz Medical Campus, Denver, CO, USA. andrew.callen@cuanschutz.edu.

Journal of Digital Imaging

|August 20, 2020

Summary

This summary is machine-generated.

Radiologists use uncertainty terms differently across imaging types and patient groups. Natural language processing accurately identifies these terms, which correlate with human interpretation of hedging.

Keywords:

Diagnostic uncertainty Natural language processing

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Area of Science:

Radiology
Medical Informatics
Natural Language Processing

Background:

Radiology reports aim to reduce diagnostic uncertainty.
Ambiguity in reports can hinder clinical decision-making.
Variability in language use among radiologists is a known issue.

Purpose of the Study:

To characterize the use of uncertainty terms in radiology reports.
To compare uncertainty term usage across modalities, anatomy, patients, and radiologists.
To assess if uncertainty terms are interpreted as hedging by human readers.

Main Methods:

Applied a natural language processing (NLP) algorithm to analyze 642,569 radiology report impressions (2011-2015).
Developed an algorithm to detect a predefined set of uncertainty terms.
Validated NLP findings with two independent radiologist reviewers.

Main Results:

Significant differences in uncertainty term use were found across patient admission status and anatomic subsections.
Reports containing uncertainty terms were significantly longer.
NLP algorithm demonstrated high accuracy (0.91) and sensitivity (0.92) compared to a gold standard reviewer.

Conclusions:

Substantial variability exists in radiologist and subspecialty use of uncertainty terms.
This variability is not explained by radiologist experience or modality proportions.
NLP detection of uncertainty terms reliably predicts human assessment of uncertainty and hedging.