Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

44.8K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
44.8K
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

38.1K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
38.1K
Data Reporting and Recording01:24

Data Reporting and Recording

5.5K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.5K
Nursing Clinical Information System01:27

Nursing Clinical Information System

1.3K
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
1.3K
Clinical Trials01:16

Clinical Trials

10.8K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
10.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Questioning accelerated hydroxychloroquine retinopathy.

Documenta ophthalmologica. Advances in ophthalmology·2024
Same author

The rapid N-wave as a potentially useful measure of the photopic negative response.

Documenta ophthalmologica. Advances in ophthalmology·2020
Same author

Riggs-type dominant congenital stationary night blindness: ERG findings, a new GNAT1 mutation and a systemic association.

Documenta ophthalmologica. Advances in ophthalmology·2018
Same author

A Novel Heterozygous Missense Mutation in <i>GNAT1</i> Leads to Autosomal Dominant Riggs Type of Congenital Stationary Night Blindness.

BioMed research international·2018
Same author

ERG and other discriminators between advanced hydroxychloroquine retinopathy and retinitis pigmentosa.

Documenta ophthalmologica. Advances in ophthalmology·2017
Same author

Bacterial contamination of ocular surface and needles in patients undergoing intravitreal injections.

Retina (Philadelphia, Pa.)·2008

Related Experiment Video

Updated: Feb 7, 2026

Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.9K

Clinical display of mfERG data.

Michael F Marmor1, Lorella Cabael2

  • 1Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, 2452 Watson Court, Palo Alto, CA, 94303, USA. marmor@stanford.edu.

Documenta Ophthalmologica. Advances in Ophthalmology
|July 22, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces the Stanford Display for multifocal electroretinography (mfERG), improving retinal disease analysis by standardizing signal scaling and utilizing a retinal view for accurate localization and simplified interpretation of mfERG results.

Keywords:
Hydroxychloroquine retinopathyRetinal viewRing ratiosRing response averagesStimulus scaling factorStretch factormfERG

More Related Videos

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
09:04

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display

Published on: January 14, 2020

10.3K
Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.9K

Related Experiment Videos

Last Updated: Feb 7, 2026

Author Spotlight: Advancing Alzheimer's Research &#8211; Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.9K
Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display
09:04

Recording Ultra-Realistic Full-Color Analog Holograms for Use in a Moving Hologram Display

Published on: January 14, 2020

10.3K
Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.9K

Area of Science:

  • Ophthalmology
  • Neuroscience
  • Medical Imaging

Background:

  • Multifocal electroretinography (mfERG) displays often present inaccurate signal representations due to non-uniform scaling and lack of clear retinal localization.
  • Traditional mfERG printouts can be misleading, using 3-D plots and variable ring response densities that hinder clinical interpretation and literature communication.

Observation:

  • The Stanford Display modifies the mfERG scaling factor to achieve near-equal signal amplitudes across the entire trace array.
  • Responses are presented in a spatially scaled array with a retinal view, ensuring signals are displayed in their correct anatomical positions relative to fundus images.

Findings:

  • The revised mfERG display facilitates easier analysis of retinal diseases by clearly localizing areas of signal loss.
  • Ring ratios, normalized to a standard value of 1.0, simplify response amplitude analysis.
  • A case study of early hydroxychloroquine retinopathy effectively demonstrates the utility of the Stanford Display.

Implications:

  • Adopting standardized mfERG recording and display options, such as proper scaling and retinal/field views, can enhance diagnostic value.
  • Improved mfERG analysis aids in the precise localization of retinal disease and simplifies interpretation of ring response data.
  • This approach can improve communication and consistency in mfERG research and clinical practice.