Related Experiment Video

Updated: Apr 19, 2026

Author Spotlight: Advancing Pathogen Detection and Disease Assessment in Real-Time Using M-ROSE
03:22

Author Spotlight: Advancing Pathogen Detection and Disease Assessment in Real-Time Using M-ROSE

Published on: March 1, 2024

1.3K

Verification and classification bias interactions in diagnostic test accuracy studies for fine-needle aspiration

Robert L Schmidt1, Brandon S Walker, Michael B Cohen

  • 1Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah.

Cancer Cytopathology
|December 19, 2014
PubMed
Abstract

Keywords:
classification biasdiagnostic accuracyfine-needle biopsyinteractionsverification bias

More Related Videos

Detection of Extravascular Trypanosoma Parasites by Fine Needle Aspiration08:33

Detection of Extravascular Trypanosoma Parasites by Fine Needle Aspiration

Published on: August 7, 2019

9.8K
Use of Electromagnetic Navigational Transthoracic Needle Aspiration E-TTNA for Sampling of Lung Nodules06:03

Use of Electromagnetic Navigational Transthoracic Needle Aspiration E-TTNA for Sampling of Lung Nodules

Published on: May 23, 2015

23.0K

Related Concept Videos

Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.7K
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
1.9K
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
587
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.9K
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
8.1K