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

Pulse Assessment Sites01:11

Pulse Assessment Sites

Pulse assessment sites are crucial in evaluating a patient's cardiovascular health. By assessing the pulsations of arteries at specific anatomical locations, healthcare professionals can gather valuable information about blood flow, heart rate, and peripheral circulation. Understanding these pulse assessment sites is essential for conducting comprehensive cardiovascular evaluations and monitoring patients' overall health. These sites are strategically chosen due to the accessibility and...
Assessment of apical pulse01:17

Assessment of apical pulse

Assessing the Apical Pulse
Assessing the apical pulse is a critical nursing procedure, particularly indicated for:
Assessment of apical radial pulse01:25

Assessment of apical radial pulse

Apical-Radial (A-R) Pulse Assessment
The A-R pulse assessment involves simultaneous evaluation of the apical and radial pulses. When the apical and radial pulse rates vary, this assessment helps identify a pulse deficit.
Pre-Procedural Preparation
Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

Assessment of Ventilation II: Respiratory Depth and Rhythm

Respiratory Depth
Respiratory depth measures the volume of air inhaled or exhaled during a breath. It can vary from shallow to deep and typically remains consistent when a person is at rest or asleep. Occasionally, individuals will automatically inhale deeply, known as sighing, which inflates the lungs with more air than normal breathing.
To assess respiratory depth, observe the degree of chest excursion or movement:
Assessment of the Cardiovascular System IV: Auscultation01:25

Assessment of the Cardiovascular System IV: Auscultation

Cardiac auscultation is a clinical skill used to assess heart function and detect abnormalities. It involves listening to heart sounds at specific anatomical locations through a stethoscope.
Normal Heart Sounds
S1 (First Heart Sound)-
S1 is made by the closure of the mitral and tricuspid valves (atrioventricular valves), marking the beginning of systole.
S2 (Second Heart Sound)-
S2 is made by the closure of the aortic and pulmonic valves (semilunar valves), marking the end of the systole.
Cardiac Catheterization II: Right Heart Catheterization01:21

Cardiac Catheterization II: Right Heart Catheterization

Right Heart Catheterization: An OverviewRight heart catheterization is an invasive diagnostic procedure that measures right-sided cardiac and pulmonary artery pressures, calculates cardiac output, and identifies intracardiac shunts. It provides detailed hemodynamic data essential for diagnosing and managing various cardiovascular conditions, such as pulmonary hypertension.Access SitesCommon access sites for right heart catheterization include the internal jugular vein in the neck region, the...

You might also read

Related Articles

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

Sort by
Same author

Proceedings from the 2025 Midwest Pediatric Device Consortium showcase featuring software as a medical device.

BMC proceedings·2026
Same author

Use of and Experience With Wearable Biosensors in Congenital Heart Disease: A Survey Study.

CJC pediatric and congenital heart disease·2026
Same author

Hybrid rule-based and on-premises LLM pipeline for extracting CMR and CPET metrics from free-text reports in repaired tetralogy of Fallot.

medRxiv : the preprint server for health sciences·2026
Same author

AI learning for pediatric right ventricular assessment: development and validation across multiple centers.

NPJ digital medicine·2025
Same author

Free-Breathing Multi-Slice Co-Registered Cardiac T1, T2, and ADC Mapping With Spin-Echo Echo Planar Imaging.

Magnetic resonance in medicine·2025
Same author

Supervised Machine Learning Models Predicting Postoperative Low Cardiac Output Syndrome In Neonates.

Critical care explorations·2025

Related Experiment Video

Updated: Jul 17, 2026

Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography
07:11

Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography

Published on: October 28, 2020

2.8K

AI Learning for Pediatric Right Ventricular Assessment: Development and Validation Across Multiple Centers.

Charitha Reddy, Yi Yan, Min Qiu

    Medrxiv : the Preprint Server for Health Sciences
    |March 31, 2025
    PubMed
    Summary

    An AI tool automates right ventricular (RV) function assessment in children, achieving expert-level accuracy. This technology improves diagnosis and management of pediatric heart conditions, especially in underserved areas.

    More Related Videos

    Hemodynamic Precision in the Neonatal Intensive Care Unit using Targeted Neonatal Echocardiography
    09:31

    Hemodynamic Precision in the Neonatal Intensive Care Unit using Targeted Neonatal Echocardiography

    Published on: January 27, 2023

    822
    Author Spotlight: Establishment and Confirmation of a Postnatal Right Ventricular Volume Overload Mouse Model
    06:04

    Author Spotlight: Establishment and Confirmation of a Postnatal Right Ventricular Volume Overload Mouse Model

    Published on: June 9, 2023

    995

    Related Experiment Videos

    Last Updated: Jul 17, 2026

    Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography
    07:11

    Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography

    Published on: October 28, 2020

    2.8K
    Hemodynamic Precision in the Neonatal Intensive Care Unit using Targeted Neonatal Echocardiography
    09:31

    Hemodynamic Precision in the Neonatal Intensive Care Unit using Targeted Neonatal Echocardiography

    Published on: January 27, 2023

    822
    Author Spotlight: Establishment and Confirmation of a Postnatal Right Ventricular Volume Overload Mouse Model
    06:04

    Author Spotlight: Establishment and Confirmation of a Postnatal Right Ventricular Volume Overload Mouse Model

    Published on: June 9, 2023

    995

    Area of Science:

    • Cardiology
    • Artificial Intelligence in Medicine
    • Pediatric Cardiovascular Health

    Background:

    • Congenital and acquired heart disease impacts approximately 1% of children globally, with right ventricular (RV) dysfunction posing a significant clinical challenge.
    • Accurate RV assessment in pediatric patients is complex due to unique cardiac geometry, interventricular interactions, and morphological variability.
    • Fractional area change (FAC) is a crucial echocardiographic metric for assessing RV function severity and guiding treatment in pediatric heart disease.

    Purpose of the Study:

    • To develop and validate an artificial intelligence (AI) framework for automated RV assessment in pediatric echocardiograms.
    • To enhance the accuracy and standardization of RV function quantification, including fractional area change (FAC).
    • To extend the AI framework's capabilities to improve left ventricular (LV) functional assessment and cardiac abnormality identification, such as pulmonary hypertension (PH).

    Main Methods:

    • Utilized a large dataset of 24,984 echocardiograms from 3,993 pediatric patients across North American and Asian tertiary care centers.
    • Developed a multi-task learning AI framework for automated RV segmentation, beat-by-beat RV FAC quantification, and PH identification.
    • Validated the AI framework's performance against expert annotations and across diverse patient cohorts.

    Main Results:

    • The AI system achieved high Dice similarity coefficients for RV segmentation (0.86 A4C, 0.88 PSAX), comparable to expert performance.
    • Demonstrated robust RV functional assessment with Area Under the Curve (AUC) values of 0.95 (U.S.) and 0.97 (Asian cohort).
    • Achieved high diagnostic accuracies for PH classification (0.95 U.S., 0.94 Asian) and significantly improved LV ejection fraction (EF) prediction.

    Conclusions:

    • The validated AI framework provides reliable, automated ventricular function analysis at an expert level for pediatric patients.
    • This technology has the potential to streamline clinical workflows and standardize cardiac assessments, improving care for pediatric cardiovascular disorders.
    • The AI framework offers particular benefits for improving pediatric cardiac care in resource-limited settings.