AI-Driven Data Management on Distributed Computing for Digital Healthcare
Akdemir, Bilgehan (2024-04-23)
IEEE
23.04.2024
B. Akdemir, "AI-Driven Data Management on Distributed Computing for Digital Healthcare," 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, 2024, pp. 251-252, doi: 10.1109/PerComWorkshops59983.2024.10502691
https://rightsstatements.org/vocab/InC/1.0/
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202501081093
https://urn.fi/URN:NBN:fi:oulu-202501081093
Tiivistelmä
Abstract
This research aims to optimize the processing of medical data by developing and implementing an efficient distributed computing platform by leveraging machine learning and edge computing. By doing so, we seek to strike a balance between the computational requirements of machine learning models and the need to process medical data locally in many mobile medical imaging scenarios, thus addressing the challenges posed by volume, privacy, and security.
This research aims to optimize the processing of medical data by developing and implementing an efficient distributed computing platform by leveraging machine learning and edge computing. By doing so, we seek to strike a balance between the computational requirements of machine learning models and the need to process medical data locally in many mobile medical imaging scenarios, thus addressing the challenges posed by volume, privacy, and security.
Kokoelmat
- Avoin saatavuus [38865]