CardioLearn: an interactive R shiny application for foundational cardiology education

Introduction

Globally, cardiovascular disease (CVD) is the leading cause of mortality, with an estimated 19.42 million deaths attributed to CVD.¹ This highlights the growing global burden of CVD and underscores the critical importance of comprehensive and effective education in cardiovascular concepts for medical students and trainees. Fundamental topics such as the cardiac cycle, cardiovascular anatomy, and physiology are essential to clinical competence; however, they are often cited as challenging areas for students and remain a persistent knowledge gap.^2–3 These challenges may appear more clearly during the practical application of these concepts to clinical scenarios and examinations. Traditional methods alone may not adequately support the comprehensive undertaking of complex medical concepts and may require supplementary learning modalities. Interactive learning tools and AI-driven simulations have shown promise in bridging this educational gap through improving student engagement and facilitating a deeper understanding.⁴ Interactive virtual learning tools and simulations allow students to learn and understand in a safe environment, free from the pressure of a formal teaching setting. Students can tailor their learning to suit their needs and preferred learning styles. Reflecting this, the use of simulated and virtual learning environments is increasingly adopted by medical educators to supplement traditional methods and reinforce understanding.⁵

Many tools have been developed to address these challenges in cardiology education through virtual learning and/or simulation. For example, the Harvey Cardiopulmonary Simulator has been used in a clinical education setting to simulate a range of cardiac findings, although its use is typically restricted to physical simulators in institutional settings.⁶ More recently, online platforms such as Human BioDigital offer passive visualisation of cardiovascular anatomy and physiology, but lack engaging and interactive learning modules.⁷ In contrast, CardioLearn aims to provide a fully open-source, browser-based environment that combines visual simulation, interactivity, self-assessment, and clinical reasoning to support active learning in the foundations of cardiology.

CardioLearn is an interactive web-based application built using the R programming language and the Shiny framework, designed to supplement understanding of cardiology principles in medical education. CardioLearn integrates several learning modalities to cover foundational aspects of cardiology and bridge the gap between theoretical knowledge and clinical application. These include a visual exploration of the cardiac cycle through an interactive Wiggers diagram, a formative self-assessment quiz to reinforce conceptual understanding, a simplified interactive 3D model illustrating left atrial dynamics, and a series of clinical case studies. Cardiolearn is designed to be an accessible, open-access supplementary resource for medical students seeking to strengthen their understanding of essential cardiology. Cardiolearn is a scalable and effective teaching modality that can be widely adopted, serving as both a self-directed learning resource for students and a teaching aid for educators.

Methods

Cardiac cycle module

This module utilises predefined data (cardiac_phases, Wiggers_data) to generate an annotated, interactive Wiggers diagram. Users can select a specific phase of the cardiac cycle, which is then highlighted on the diagram, along with a textual description of the anatomical and physiological events that occur during that phase ( Figure 1). The Wiggers diagram plots are simplified representations of ECG voltage, aortic pressure, ventricular pressure, atrial pressure, and ventricular volume against normalised time to enhance comparative learning across phases.

Figure 1. Cardiac Cycle module with interactive Wiggers diagram Interface.

The Cardiac Cycle module displays an interactive Wiggers diagram, allowing specific phases to be selected - as illustrated for atrial systole. Users can explore synchronised ECG, pressure, and volume curves across a normalised cardiac cycle, supported by descriptive annotations to reinforce phase-specific physiology.

Quiz module

A list of multiple-choice questions (quiz_questions) is accessible within the application. The user interface dynamically renders one question at a time, and the server logic evaluates the user’s answer, provides immediate feedback, and tracks the score ( Figure 2).

Figure 2. Quiz Module Interface in CardioLearn.

The Quiz module displays a single best answer multiple-choice question to allow users to self-assess their knowledge. Users select their response and receive immediate feedback upon submission.

3D heart model

This module utilises the rgl package to create a simplified 3D representation, focusing on the left atrium (LA). Users can adjust a slider representing “Left Ventricular Function” (in percentage terms). Reduced left ventricular (LV) function conceptually leads to an increase in the displayed left atrial (LA) size, as indicated by both diameter and 3D model radius. Users can also select the “LA Cycle Phase” (Filling or Ejection). These inputs dynamically alter: The 3D LA model’s appearance (colour) and simulated blood flow direction (represented by coloured lines for pulmonary vein inflow and LA to LV outflow). The state of a conceptual mitral valve (open/closed, represented by a colored sphere) ( Figure 3).

Figure 3. Three-dimensional Left Atrial Model.

This module displays a 3D model of the left atrium, with user-controlled left ventricular (LV) function and atrial phase. The model in this figure shows 70% LV function during diastolic filling. The 3D model visualises chamber size and flow, while the pressure-volume loop illustrates hemodynamic changes linked to ventricular performance and atrial phase.

Clinical cases module

This section presents users with brief clinical scenarios (clinical_cases), each followed by a multiple-choice question asking for the most likely diagnosis. The application provides feedback and an explanation for the correct answer ( Figure 4).

Figure 4. Clinical Case Module Interface.

The Clinical Cases module interface displays a series of single-best-answer multiple-choice questions based on clinical scenarios. Users can apply their clinical knowledge and test themselves.

Use cases

CardioLearn is intended for undergraduate medical students as a supplementary tool to their existing curriculum.

Visualising the Cardiac Cycle: Students can select “Isovolumetric Contraction” from the dropdown in the “Cardiac Cycle” module. The Wiggers diagram will highlight the corresponding time interval, and the description will explain that the ventricles contract with all valves closed. This helps correlate ECG events, pressure changes, and volume changes visually, allowing students to easily digest the information. Self-Assessment of Knowledge: In the “Quiz” module, a student might encounter the question, “Which ECG wave represents atrial depolarisation?” They select an option and click “Submit.” If correct, they receive positive feedback; if incorrect, the correct answer is provided. This allows for low-stakes formative assessment. Exploring Anatomical and Physiological Relationships (3D Model): A student navigates to the “3D Heart Model.” Input 1: They set “Left Ventricular Function” to 30% (simulating heart failure) and “LA Cycle Phase” to “Filling.”

Output 1: The 3D LA model appears enlarged, colored to indicate filling, with simulated flow from pulmonary veins and an open mitral valve. The associated “Diastolic Filling (E/A Wave)” plot shows a predominant A wave (or an increased E/A ratio, depending on the specific impairment logic), and the “LA Pressure-Volume Loop” is shifted upward and to the right, indicating higher pressures and volumes. Input 2: They then change “LA Cycle Phase” to “Ejection”. Output 2: The 3D LA model changes colour, flow is shown towards the conceptual LV, and the mitral valve closes. The corresponding points on the 2D curves would be highlighted if such interactive linking were implemented for the current phase.

Developing Clinical Reasoning: In the “Clinical Cases” module, students read a scenario describing a patient with crushing chest pain and ST-elevation on the ECG. They are asked for the most likely diagnosis. Upon selecting “Myocardial Infarction” and submitting, they receive confirmation and a brief explanation reinforcing the link between symptoms, ECG findings, and the diagnosis.

Discussion

CardioLearn provides an interactive, multi-modal educational platform for medical students to explore fundamental cardiology concepts. By integrating visual diagrams, a 3D anatomical model, self-assessment quizzes, and clinical scenarios, it aims to cater to diverse learning preferences and promote active engagement with the material. The focus on left atrial dynamics in the 3D module, while simplified, offers a unique way to visualise the interplay between ventricular function and atrial remodelling, as well as the phases of atrial mechanical function.

Conclusion

CardioLearn provides a valuable and engaging supplementary resource for medical students embarking on their journey into the field of cardiology.

Ethical statement

All clinical cases presented in the application are hypothetical and constructed for educational purposes. No real patient data was used in the development of this tool.

Software availability

The R source code for the CardioLearn Shiny application (app.R) is available on GitHub. The application can be run locally by cloning the GitHub repository and running the app.R file within an R environment with all required packages installed (shiny, shinythemes, ggplot2, dplyr, DT, markdown, rgl). It is also hosted publicly.

Software available from: https://connect.posit.cloud/786miii/content/0197370c-7a22-98e9-dd38-66571d2ad4be

Source code available from: https://github.com/mahmood789/Cardiac3d

Archived source code: https://doi.org/10.5281/zenodo.15742898 (Mahmood A. CardioLearn: An Interactive R Shiny Application for Foundational Cardiology Education (1.0) [dataset]. Zenodo; 2025. Available from: https://doi.org/10.5281/zenodo.15742898)¹⁷

License: Apache License 2.0

Units, symbols and mathematical scripts

Standard medical and physiological units are used where implied (e.g., mmHg for pressure, % for ejection fraction). The 3D model coordinates are in arbitrary rgl units designed for visualisation. No complex mathematical scripts are presented outside the inherent logic within the R code.