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Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial

Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial

This tutorial paper aims to fill that gap by providing a sequence of step-by-step instructions, supported by complementary demo code, to assist those practitioners who are not specialized in this area to effectively translate state-of-the-art research in synthetic EHR data to practical applications. This tutorial is designed with the expectation that readers have a basic understanding of ML concepts and proficiency in Python programming.

Chao Yan, Ziqi Zhang, Steve Nyemba, Zhuohang Li

JMIR AI 2024;3:e52615

Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial

Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial

However, gaps in comprehensive tutorials including complete codesets with relevant tutorial data are less well disseminated. Tutorials that move beyond simulated data or laboratory-based samples to real-world health care data sets might add to the understanding of these important methods while catalyzing the modeling community to apply these guides directly in their work using the published code.

Drew Wilimitis, Colin G Walsh

JMIR AI 2023;2:e49023

Assessing Facilitator Fidelity to Principles of Public Deliberation: Tutorial

Assessing Facilitator Fidelity to Principles of Public Deliberation: Tutorial

The purpose of this tutorial, therefore, is to present the blueprint we developed to systematically assess facilitator remarks made during a public deliberation about the acceptability of allowing minor consent for biomedical HIV prevention research. We briefly describe the deliberation, present the coding templates, list the analytic procedures, describe the assessment results from 1 deliberation site, and provide examples of how the assessment results were used to optimize future deliberations.

Claire Draucker, Andrés Carrión, Mary A Ott, Amelia Knopf

JMIR Form Res 2023;7:e51202

An Emerging Screening Method for Interrogating Human Brain Function: Tutorial

An Emerging Screening Method for Interrogating Human Brain Function: Tutorial

tutorialTutorial TutorialAn Emerging Screening Method for Interrogating Human Brain Function: Tutorial

Gustavo Sudre, Anto I Bagić, James T Becker, John P Ford

JMIR Form Res 2023;7:e37269

Creating a Successful Virtual Reality–Based Medical Simulation Environment: Tutorial

Creating a Successful Virtual Reality–Based Medical Simulation Environment: Tutorial

Through our experience launching VR-based clinical simulation sessions in hospitals such as the Sunnybrook Health Sciences Centre, the Hospital for Sick Children, and the Sunnybrook Canadian Simulation Centre, this tutorial aims to provide educators with a series of practical suggestions for designing and implementing VR-based medical education sessions (Textbox 1).

Sanchit Gupta, Kyle Wilcocks, Clyde Matava, Julian Wiegelmann, Lilia Kaustov, Fahad Alam

JMIR Med Educ 2023;9:e41090

The Healing Hearts Together Randomized Controlled Trial and the COVID-19 Pandemic: A Tutorial for Transitioning From an In-Person to a Web-Based Intervention

The Healing Hearts Together Randomized Controlled Trial and the COVID-19 Pandemic: A Tutorial for Transitioning From an In-Person to a Web-Based Intervention

This tutorial aims to help clinical researchers transition their in-person research programs to a web-based format during the pandemic and beyond. To our knowledge, no literature exists on how to navigate the steps required to transition a randomized controlled trial (RCT), designed for in-person delivery, to an online world. No one has outlined, for example, contacts with sponsors and research ethics boards, recruitment procedures, or informed consent changes.

Kathleen Lalande, Paul S Greenman, Karen Bouchard, Susan M Johnson, Heather Tulloch

J Med Internet Res 2021;23(4):e25502

Building a Secure Biomedical Data Sharing Decentralized App (DApp): Tutorial

Building a Secure Biomedical Data Sharing Decentralized App (DApp): Tutorial

This tutorial presents a mobile i OS DApp that allows a research study participant (participant) to share useful features of their location data derived from global positioning system (GPS) coordinates, or geocoordinates, with a research team (third party), without revealing their raw GPS coordinates.

Matthew Johnson, Michael Jones, Mark Shervey, Joel T Dudley, Noah Zimmerman

J Med Internet Res 2019;21(10):e13601