The role of trustworthy and reliable AI for multiple sclerosis
This paper investigates the importance of Trustworthy Machine Learning (ML) in the context of Multiple Sclerosis (MS) research and care. Due to the complex and individual nature of MS, the need for reliable and trustworthy ML models is essential. In this paper, key aspects of trustworthy ML, such as...
Saved in:
| Main Authors: | Lorin Werthen-Brabants, Tom Dhaene, Dirk Deschrijver |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-03-01
|
| Series: | Frontiers in Digital Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1507159/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
From theory to practice: Harmonizing taxonomies of trustworthy AI
by: Christos A. Makridis, et al.
Published: (2024-12-01) -
Achieving On-Site Trustworthy AI Implementation in the Construction Industry: A Framework Across the AI Lifecycle
by: Lichao Yang, et al.
Published: (2024-12-01) -
Establishing and evaluating trustworthy AI: overview and research challenges
by: Dominik Kowald, et al.
Published: (2024-11-01) -
AI_TAF: A Human-Centric Trustworthiness Risk Assessment Framework for AI Systems
by: Eleni Seralidou, et al.
Published: (2025-06-01) -
AI Trustworthiness in Manufacturing: Challenges, Toolkits, and the Path to Industry 5.0
by: M. Nadeem Ahangar, et al.
Published: (2025-07-01)