197. Technology Opportunity Discovery for Smart Healthcare
Invited abstract in session MB-13: Medical services and applications, stream OR in Healthcare (ORAHS).
Monday, 10:30-12:00Room: Clarendon SR 1.01
Authors (first author is the speaker)
| 1. | Yucheol Kim
|
| Industrial Engineering, Yonsei University | |
| 2. | Hyungsuk Lim
|
| Industrial Engineering, Yonsei University | |
| 3. | Geon Hyeok Chun
|
| Industrial Engineering (Industrial Statistics Lab), Yonsei University | |
| 4. | So Young Sohn
|
| Industrial Engineering, Yonsei university |
Abstract
Smart healthcare is a rapidly expanding field with potential of providing personalized and cost-effective healthcare solutions. Despite the rising attention in smart healthcare, most previous studies that focus on identifying innovative opportunities in smart healthcare only offer fragmented approaches as they neglect the integration of biological and technological perspectives. In this study, we propose a novel framework that can predict future innovations in smart healthcare based on disease co-occurrence pattern in smart healthcare technologies. Our framework leverages time-dynamic link prediction within a multiplex disease co-occurrence network that incorporates diverse relationship between diseases. In the link prediction process, we compare various network embedding models and window strategies to optimize the performance of predicting disease co-occurrence patterns. Additionally, we utilize community detection to uncover potential technologies that are capable of effectively addressing previously unobserved combinations of diseases.
Keywords
- Medical Applications
- Analytics and Data Science
- Artificial Intelligence
Status: accepted
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