GenDatr: Visualizing Probabilistic Data Generation in Medical Data Science

Zong Poh Loo, Ang Kang Tan, Clement Jun Kai Choo, Shaun Jia Le Tay, Xue Er Lim, Jeremiah Xian Ming Loh, Andrew Ge-Hall, Peter Chun Yu Yau, Dennis Wong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The PERN stack is a robust technology stack for modern web application development. It comprises PostgreSQL, Express.js, React, and Node.js. This project introduces the GenDatr web application, showcasing Integrant Labs’ innovative pursuits. As a Single Page Application (SPA), it seamlessly integrates new data insights and predictive models, enhancing user experience. PostgreSQL ensures robust data management, Express.js facilitates efficient backend server and API development, React enables dynamic and user-friendly interfaces, Node.js supports scalable server-side execution. By employing Agile Methodology, we ensured iterative progress and adaptability throughout the project’s phases. Together, these components ensure the GenDatr application is robust, efficient, and scalable, reflecting GenDatr’s commitment to advancing research and development through an immersive, interactive platform.

Original languageEnglish
Title of host publicationProceedings of the Future Technologies Conference (FTC) 2024
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages373-378
Number of pages6
ISBN (Print)9783031731242
DOIs
Publication statusPublished - 2024
Event9th Future Technologies Conference, FTC 2024 - London, United Kingdom
Duration: 14 Nov 202415 Nov 2024

Publication series

NameLecture Notes in Networks and Systems
Volume1156 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference9th Future Technologies Conference, FTC 2024
Country/TerritoryUnited Kingdom
CityLondon
Period14/11/2415/11/24

Keywords

  • Express
  • Node
  • PERN
  • PostgreSQL
  • Predictive models
  • React
  • Single page application
  • Visualization

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