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Related Concept Videos

Transcription01:17

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Transcription01:10

Transcription

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Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

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Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
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Errors in Taping01:18

Errors in Taping

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Errors in taping arise from multiple factors that can significantly impact measurement accuracy in surveying. Misalignment of the tape, often due to human error, is one primary source. A skilled rear tapeman, using a telescope, can help correct alignment by guiding the head tapeman; however, human limitations still lead to small inaccuracies. These errors may include misplacement of pins or inaccurate tape readings due to common visual confusions, such as mistaking a six for a nine. Such...
446
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

933
Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of...
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Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

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When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
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Related Experiment Video

Updated: Mar 29, 2026

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors
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Syntactic and semantic errors in radiology reports associated with speech recognition software.

Michael D Ringler1, Brian C Goss1, Brian J Bartholmai1

  • 1Mayo Clinic, USA.

Health Informatics Journal
|December 5, 2015
PubMed
Summary

Speech recognition software in radiology reports leads to errors affecting patient care. Quality control programs and feedback can significantly reduce these errors over time.

Keywords:
PowerScribequality controlradiology reportreport errorsspeech recognition

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Area of Science:

  • Medical Informatics
  • Radiology

Background:

  • Speech recognition software (SRS) is widely used in radiology.
  • SRS can introduce errors into radiology reports, potentially impacting patient care.

Purpose of the Study:

  • To quantify the frequency and types of errors in SRS-generated radiology reports.
  • To identify factors associated with error rates, including radiologist, subspecialty, and report type.

Main Methods:

  • Analysis of 213,977 SRS-generated radiology reports from 147 radiologists.
  • Classification of errors as material (altering interpretation) or immaterial (intrusion/omission, spelling).
  • Statistical comparison of error proportions across radiologists, subspecialties, and time periods.

Main Results:

  • 9.7% of reports contained errors, with 1.9% classified as material.
  • Spelling errors were more common than intrusion/omission errors among immaterial errors.
  • Error rates varied significantly among radiologists and subspecialties, and were higher in cross-sectional, reinterpretation, and procedural reports.

Conclusions:

  • SRS use in radiology is associated with a notable rate of errors, including material ones.
  • Error rates are influenced by radiologist, subspecialty, and report type.
  • A quality control program with feedback appears effective in reducing SRS-related errors in radiology reports over time.