Metastatic malignant nerve sheath tumour in a dog
Veterinary Record Case Reports, Volume 14, Issue 2, May 2026.Abstract A 5‐year‐old, male, English Cream Golden Retriever dog with a 3‐month history of left thoracic limb lameness was presented to the University of Georgia Veterinary Teaching Hospital. Physical examination was unremarkable. Neurological examination indicated a left peripheral C6‒T2 lesion, but further diagnostics were declined in favour of ...
Samantha Gomez +4 more
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Minimizing Task Age upon Decision for Low-Latency MEC Networks Task Offloading with Action-Masked Deep Reinforcement Learning. [PDF]
Sensors (Basel)Jiang Z, Yang J, Gao X.
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Implementing AI in Radiotherapy: Insights From the Healthcare Professions
Sociology of Health &Illness, Volume 48, Issue 4, May 2026.ABSTRACT The potential for artificial intelligence (AI) to transform healthcare has been of growing academic, policy and professional interest. Various studies have reported on the perceptions of the potential for AI in healthcare. However, fewer studies have examined the lived experiences that healthcare professionals (HCPs) have with the use of AI ...
Juan I. Baeza +3 more
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Energy Efficiency Optimisation of Joint Computational Task Offloading and Resource Allocation Using Particle Swarm Optimisation Approach in Vehicular Edge Networks. [PDF]
Sensors (Basel)Alam A +4 more
europepmc +1 more source
A decision-making mechanism for task offloading using learning automata and deep learning in mobile edge networks. [PDF]
HeliyonTan X +6 more
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Multi-Agent Deep Reinforcement Learning Based Dynamic Task Offloading in a Device-to-Device Mobile-Edge Computing Network to Minimize Average Task Delay with Deadline Constraints. [PDF]
Sensors (Basel)He H, Yang X, Mi X, Shen H, Liao X.
europepmc +1 more source
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Task Offloading with Task Classification and Offloading Nodes Selection for MEC-Enabled IoV
ACM Transactions on Internet Technology, 2021The Mobile Edge Computing (MEC)-based task offloading in the Internet of Vehicles (IoV) scenario, which transfers computational tasks to mobile edge nodes and fixed edge nodes with available computing resources, has attracted interest in recent years. The MEC-based task offloading can achieve low latency and low operational cost under the tasks delay ...
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Task Offloading with Uncertain Processing Cycles
Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, 2021Mobile Edge Computing (MEC) has emerged to be an integral component of 5G infrastructure due to its potential to speed up task processing and reduce energy consumption for mobile devices. However, a major technical challenge in making offloading decisions is that the number of required processing cycles of a task is usually unknown in advance.
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Toward Intelligent Task Offloading at the Edge
IEEE Network, 2020With the booming development of IoT and massive smart MDs springing up in daily life, the conflict between resource-hungry IoT applications and resource-constrained MDs becomes increasingly prominent. To cope with compute-intensive applications and big data, MCC combining AI was adopted as a workable solution.
Hongzhi Guo +2 more
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Scheduling with task duplication for application offloading
2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), 2017Computation offloading frameworks partition an application's execution between a cloud server and the mobile device to minimize its completion time on the mobile device. An important component of an offloading framework is the partitioning algorithm that decides which tasks to execute on mobile device or cloud server.
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