Medical Data Processing System Dynamic Service Prioritization
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Solution Overview
Problem
The inefficiency in executing medical data analyzing services due to limited computational resources, where urgent services are delayed, and user preferences are not adequately met, leading to suboptimal use of resources and workflow inefficiencies among radiologists.
Innovation Solution
A medical data processing system that utilizes user feedback through a reinforcement learning approach to optimize the execution of analyzing services by controlling which services are executed, the computational resources allocated, and scheduling, based on usage data and hospital policies, ensuring that services are prioritized and configured to meet user-specific needs and hospital protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If analyzing services are executed in first-in-first-out order, then processing order is simple, but urgent analyzing services are delayed
Solution Approach 1:
The patent implements dynamic prioritization of analyzing services based on urgency levels and user preferences. The system continuously adjusts the execution order of analyzing services rather than following a static first-in-first-out queue, allowing urgent services to be prioritized and executed sooner while maintaining operational simplicity through automated decision-making algorithms.
2Adaptability or versatility
If multiple analyzing services are executed on all incoming medical data, then user preferences are met, but computational resources are wasted
Solution Approach 1:
The patent applies local quality by customizing the execution of analyzing services according to specific user preferences and requirements. Instead of uniformly applying all analyzing services to all medical data, the system selectively executes only the relevant services for each user and data type, optimizing computational resource allocation while maintaining adaptability to individual user needs.
Solution Approach 2:
The system dynamically changes parameters such as which analyzing services to execute, based on user profiles, data characteristics, and resource availability. This parameter adjustment allows the system to adapt to different users and situations without wasting computational resources on unnecessary analyses.
3Device complexity
If analyzing services are executed based on request order, then resource allocation is simple, but efficiency is reduced
Solution Approach 1:
The patent incorporates feedback mechanisms that monitor user interactions with analyzing service results and use this information to optimize future resource allocation decisions. The system learns from user behavior patterns and adjusts its resource allocation strategy accordingly, improving processing efficiency while maintaining manageable complexity through data-driven decision-making.
Data Source
AI summary
A medical data processing system includes: a medical data storage configured to collect one or more pieces of medical data from one or more input devices, a data analyzer configured to execute one or more analyzing services on the one or more pieces of medical data so as to output one or more corresponding pieces of analyzed medical data, a results manager configured to collect usage data, related to how the one or more pieces of analyzed medical data are analyzed by the data analyzer and/or used by one or more users, and a processing optimizer configured to control operation of the data analyzer based on the usage data.