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

Regression Toward the Mean01:52

Regression Toward the Mean

7.0K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.0K
Multiple Regression01:25

Multiple Regression

4.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.0K
Protein Networks02:26

Protein Networks

4.5K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.5K
Correlation and Regression00:53

Correlation and Regression

3.4K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.4K
Regression Analysis01:11

Regression Analysis

8.4K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.4K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

1.6K
Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.6K

You might also read

Related Articles

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

Sort by
Same author

Comparative analysis for nutrients, flavor compounds, and lipidome revealed the edible value of pond-cultured male Pelodiscus sinensis with different ages.

Food chemistry·2024
Same author

Segmentation and visualization of left atrium through a unified deep learning framework.

International journal of computer assisted radiology and surgery·2020
Same author

Cardiac-DeepIED: Automatic Pixel-Level Deep Segmentation for Cardiac Bi-Ventricle Using Improved End-to-End Encoder-Decoder Network.

IEEE journal of translational engineering in health and medicine·2019
Same author

Photocatalytic degradation of perfluorooctanoic acid over Pb-BiFeO<sub>3</sub>/rGO catalyst: Kinetics and mechanism.

Chemosphere·2018
Same author

Development and application of metal organic framework/chitosan foams based on ultrasound-assisted solid-phase extraction coupling to UPLC-MS/MS for the determination of five parabens in water.

Analytical and bioanalytical chemistry·2018
Same author

Expression analysis of Pannexin1 channel gene in response to immune challenges and its role in infection-induced ATP release in tilapia (Oreochromis niloticus).

Fish & shellfish immunology·2018
Same journal

Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks for In-Home Activity Learning of Mild Cognitive Impairment.

IEEE journal of biomedical and health informatics·2026
Same journal

Integrating Multi-View Residue Graph and Protein Language Model for Cell-Penetrating Peptide Prediction via Global-Local Graph Aggregation and Cross-Attentive Fusion.

IEEE journal of biomedical and health informatics·2026
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Video

Updated: Feb 3, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.8K

Direct Segmentation-Based Full Quantification for Left Ventricle via Deep Multi-Task Regression Learning Network.

Xiuquan Du, Renjun Tang, Susu Yin

    IEEE Journal of Biomedical and Health Informatics
    |November 3, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Indices-JSQ, a novel deep learning model for quantitative heart analysis. It accurately measures left ventricle indices from cardiac MR images, improving heart disease diagnosis.

    More Related Videos

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    3.5K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    10.0K

    Related Experiment Videos

    Last Updated: Feb 3, 2026

    Deep Learning-Based Segmentation of Cryo-Electron Tomograms
    10:25

    Deep Learning-Based Segmentation of Cryo-Electron Tomograms

    Published on: November 11, 2022

    10.8K
    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

    Published on: November 30, 2022

    3.5K
    Deep Neural Networks for Image-Based Dietary Assessment
    13:19

    Deep Neural Networks for Image-Based Dietary Assessment

    Published on: March 13, 2021

    10.0K

    Area of Science:

    • Medical Imaging
    • Cardiology
    • Artificial Intelligence

    Background:

    • Quantitative analysis of the heart is crucial for diagnosing heart disease.
    • Current methods face challenges in precise cardiac assessment.
    • Accurate measurement of left ventricle (LV) parameters is essential for clinical evaluation.

    Purpose of the Study:

    • To develop an end-to-end deep learning model for comprehensive quantitative analysis of the left ventricle (LV).
    • To improve the accuracy and efficiency of cardiac index estimation from MR images.
    • To establish a novel approach for holonomic quantitative analysis of cardiac function.

    Main Methods:

    • Proposed a segmentation-based deep multi-task regression learning model (Indices-JSQ).
    • The model comprises two networks: Img2Contour for LV contour segmentation and Contour2Indices for multi-task regression.
    • Utilized segmented LV contours as input for estimating cardiac indices, enhancing accuracy.

    Main Results:

    • Achieved experimental results of 157 mm² for areas, 2.43 mm for dimensions, and 1.29 mm for regional wall thicknesses.
    • Demonstrated a Dice Metric of 0.87, indicating high segmentation accuracy.
    • Outperformed state-of-the-art methods in quantitative cardiac analysis.

    Conclusions:

    • The Indices-JSQ model offers a robust and accurate method for quantitative cardiac MR image analysis.
    • The approach shows significant potential for improving cardiac MR image segmentation and clinical diagnosis.
    • This method facilitates comprehensive clinical assessment and diagnosis of heart conditions.