Decentralised machine learning in healthcare and life sciences: Applying the technology acceptance model
Machine learning (ML) has significant potential for the healthcare sector. To implement novel technologies such as decentralised machine learning (DML), platform providers must overcome low acceptance levels and implementation hurdles. We used a conceptualised model for DML for healthcare and life s...
Saved in:
| Main Authors: | Katrin Förster, Tobias Strauss |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Telematics and Informatics Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772503025000131 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Navigating the Paradox of Decentralisation by Devolution: An Evaluation of Public Healthcare Service Delivery in Developing Countries
by: Adam Matiko Charles, et al.
Published: (2025-01-01) -
Effectiveness of Decentralisation by Devolution Approaches in Public healthcare services Delivery in Ilala Municipal Council and Geita Town Council, Tanzania
by: Africanus Calist Sarwatt, et al.
Published: (2025-01-01) -
Introducing the glossary of decentralised technosocial systems
by: Valeria Ferrari
Published: (2021-04-01) -
Decentralisation: a multidisciplinary perspective
by: Balázs Bodó, et al.
Published: (2021-06-01) -
Approaches to identify scenarios for data science implementations within healthcare settings: recommendations based on experiences at multiple academic institutions
by: Lillian Sung, et al.
Published: (2025-03-01)