Clinical Priority-Based Resource Pooling for Medical Computing
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Solution Overview
Problem
In medical computing systems, there is often a limited set of computational resources available for various clinical applications, leading to potential delays in executing emergency applications that require immediate processing, as non-urgent tasks may occupy these resources, impacting patient well-being.
Innovation Solution
A system that prioritizes computer applications based on clinical priority, using a prioritization component to assign tasks to resource pools and preempt lower-priority workloads to ensure timely execution of high-priority medical tasks, employing artificial intelligence and deep learning to manage computational resources effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If computational resources are shared across multiple clinical applications, then resource utilization efficiency is improved, but execution speed of emergency applications deteriorates
Solution Approach 1:
The system segments computational resources into multiple resource pools (first resource pool, second resource pool, etc.) that can be independently managed and allocated. Each resource pool can be dedicated to specific types of applications or dynamically assigned based on clinical priority, allowing simultaneous optimization for both resource utilization and emergency response speed
Solution Approach 2:
The system implements dynamic resource allocation where the assignment of applications to resource pools changes based on real-time clinical priority assessments. The resource management system can preemptively move resources or reassign pools in response to changing clinical needs, ensuring emergency applications receive necessary computational power while maintaining overall resource efficiency
2Productivity
If non-urgent tasks occupy computational resources, then overall system productivity is improved, but time sensitivity of emergency tasks deteriorates
Solution Approach 1:
The system introduces a resource management system as an intermediary layer between clinical applications and computational resources. This intermediary assesses clinical priority and mediates resource allocation accordingly, allowing non-urgent tasks to utilize resources during low-priority periods while ensuring emergency tasks can preempt resources when needed, thus maintaining both overall productivity and time sensitivity
Solution Approach 2:
The system changes the allocation parameters of computational resources based on clinical priority levels. Resource allocation is not static but adjusts according to the urgency of clinical tasks, with parameters such as resource pool assignment and preemption thresholds being modified dynamically to balance system productivity with emergency response requirements
Data Source
AI summary
Techniques regarding the management of computational resources based on clinical priority associated with one or more computing tasks are provided. For example, one or more embodiments described herein can regard a system comprising a memory that can store computer-executable components. The system can also comprise a processor, operably coupled to the memory, that executes the computer-executable components stored in the memory. The computer-executable components can include a prioritization component that can prioritize computer applications based on a clinical priority of tasks performed by the computer applications. The clinical priority can characterize a time sensitivity of the tasks. The computer-executable components can also include a resource pool component that can divide computational resources across a plurality of resource pools and can assign the computer applications to the plurality of resource pools based on the clinical priority.