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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
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Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
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Calibration Curves: Linear Least Squares01:20

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
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Calibration Curves: Correlation Coefficient01:10

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In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
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Differential Leveling01:12

Differential Leveling

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Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
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Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

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Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...
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Recent BRCAPRO upgrades significantly improve calibration.

Emanuele Mazzola1, Jonathan Chipman2, Su-Chun Cheng2

  • 1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts mazzola@jimmy.harvard.edu.

Cancer Epidemiology, Biomarkers & Prevention : a Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology
|June 4, 2014
PubMed
Summary
This summary is machine-generated.

The updated BRCAPRO risk model (version 2.0-8) improves contralateral breast cancer (CBC) prediction accuracy and calibration. This enhanced genetic risk assessment tool is recommended for clinical counseling, especially for families with a history of CBC.

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Area of Science:

  • Genetics
  • Biostatistics
  • Oncology

Background:

  • The BRCAPRO risk prediction model is crucial for assessing hereditary breast cancer risk.
  • Previous versions required updates for improved accuracy and broader applicability.

Purpose of the Study:

  • To introduce and validate the updated BRCAPRO risk prediction model (version 2.0-8).
  • To evaluate improvements in contralateral breast cancer (CBC) penetrance modeling and calibration.

Main Methods:

  • Utilized parametric survival modeling and SEER9 data deconvolution to estimate CBC penetrance functions.
  • Validated the updated model by comparing it against the previous version using Cancer Genetics Network (CGN) pedigrees.

Main Results:

  • The updated BRCAPRO model (version 2.0-8) shows similar discrimination accuracy (AUC increase of 0.0043) and slightly improved precision (RMSE decrease of 0.0108) compared to version 2.0-7.
  • Significantly improved calibration was observed, with an observed-to-expected event ratio of 0.9765 in version 2.0-8 versus 0.8910 in version 2.0-7.
  • Incorporated revised modeling for CBC penetrance, mixed ethnicity pedigrees, and adjustments for family member mastectomies.

Conclusions:

  • Version 2.0-8 of the BRCAPRO model offers enhanced accuracy and calibration for predicting breast cancer risk, particularly for contralateral events.
  • The updated model's improvements in handling diverse family structures and risk factors make it a valuable tool for genetic counseling.
  • Clinical implementation of the new BayesMendel package version is recommended, especially in populations with a high prevalence of contralateral breast cancer.