5012. Integrating Multimodal Dark Data with Dendritic Optimization for Predictive Healthcare Digital Twins and Public Health Outcomes
Invited abstract in session ME-25: OR and Health Informatics for Sustainable Societal Outcomes, stream OR for Development.
Monday, 14:15-15:45Room: HG – Hörsaal 16
Authors (first author is the speaker)
| 1. | Mabutho Sibanda
|
| Economics & Management Sciences, North West University |
Abstract
The rapid digital transformation of healthcare has produced vast volumes of data, with nearly 80% remaining “dark” and underutilised. This study proposes a framework for integrating multimodal dark data into Healthcare Digital Twins (HDTs) using dendritic computing. The approach enhances non-linear processing, feature extraction, and computational efficiency. By enabling real-time optimisation and simulation, HDTs support clinical decision-making and resource allocation. The framework further scales to population-level analytics, advancing precision medicine and public health systems.
Keywords
- Artificial Intelligence
- Big Data
- Healthcare Analytics
Status: accepted
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