This poster was featured at SAWC Fall 2024 in Las Vegas, Nevada.
Authors: Azeem Lakdawalla, Heba Tallah Mohammed, Justin Allport, Rob D. J. Fraser
Introduction: Measuring wound dimensions through traditional methods can be time-consuming and prone to human error. Integrating artificial intelligence (AI) into Digital Wound Care Solution (DWCS) provides a model for practice improvement optimizing management plans and care delivery and making the assessment process faster and more accurate.
Objective: The study aimed to improve the performance of AI-powered wound depth measurement on a range of older smartphones and tablets, which are commonly used by healthcare organizations.鈥� Algorithm performance was tested on data from 2,050 wound evaluations of different types.鈥�
Results:
- Depth measurement runtimes improved across iOS and Android devices鈥�.
- Depth assessment times improvement tested on a commonly used Android Tablet (Samsung A7, 2015) was 5.75 times faster鈥�.
- Testing on a commonly used older model of iOS device (iPhone XR) was improved by 1.48 times鈥�.
To learn more about the research conducted for this poster, or to speak with the 91桃色视频 team about digital wound care, contact us.
