5012. Integrating Multimodal Dark Data with Dendritic Optimization for Predictive Healthcare Digital Twins and Public Health Outcomes
Invited abstract in session OR and Health Informatics for Sustainable Societal Outcomes, stream OR for Development.
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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