Global Data Center and Local Autonomous Cell Diagnostic System
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Solution Overview
Problem
Current diagnostic methods for severe pathological conditions such as breast cancer, acute myocardial infarction, and neurological strokes often lack early detection capabilities, leading to late diagnoses and ineffective treatments.
Innovation Solution
The implementation of a diagnostic system comprising local autonomous cells (LACs) equipped with measurement equipment and a global data center (GDC) that processes and categorizes data into clusters for diagnostic indicators. This system allows for the collection and analysis of local patient data, which is then compared to global data clusters to determine diagnostic indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If local diagnostic facilities are established, then accessibility to diagnostic tools is improved, but diagnostic accuracy and reliability deteriorate due to lack of comprehensive data
Solution Approach 1:
The diagnostic system is segmented into local autonomous cells that perform initial data collection and processing, then transmit results to a global data center for comprehensive analysis. This segmentation allows diagnostic tools to be distributed locally (improving accessibility) while maintaining centralized quality control (preserving accuracy).
Solution Approach 2:
The global data center acts as an intermediary between local diagnostic facilities and comprehensive diagnostic expertise. Local cells send measurement data to the global center, which processes the data against extensive reference databases and returns diagnostic indicators, thereby bridging the gap between limited local capabilities and needed diagnostic reliability.
2Reliability
If comprehensive global data processing is implemented, then diagnostic accuracy is improved, but system complexity and data processing time worsen
Solution Approach 1:
The global data center pre-processes and categorizes extensive global measurement data into organized data clusters before receiving local patient data. This preliminary organization of reference data (by disease type, demographic factors, measurement parameters) reduces the complexity of real-time diagnostic processing while maintaining comprehensive analytical capability.
3Reliability
If extensive global data is collected and processed, then diagnostic reliability is improved, but data processing time and computational resources worsen
Solution Approach 1:
The global data center performs preliminary processing of extensive global data, organizing it into pre-categorized data clusters before diagnostic queries arrive. This advance organization significantly reduces the time needed to process individual patient cases while maintaining comprehensive data analysis for reliable diagnostics.
Solution Approach 2:
Instead of processing all global raw data for each diagnostic query, the system creates and maintains simplified copies in the form of structured data clusters that capture essential diagnostic patterns. These copied representations enable rapid comparison with local patient data while preserving the diagnostic insights from comprehensive global data.
Data Source
AI summary
The techniques described herein relate to systems and methods for diagnosing diseases in human patients. In some cases, a method includes providing a set of global data to a global data center and processing the set of global data and categorizing it into data clusters, where each data cluster corresponds to a diagnostic indicator for assessment of a physiological or pathological condition. The method can further include measuring data of a local patient using measurement equipment of a local autonomous cell and communicating the local measurement data from the local autonomous cell to the global data center. The local measurement data can be processed, and the processed local measurement data can be compared with the data clusters to determine a local diagnostic indicator for the local patient. The local diagnostic indicator can then be communicated from the global data center to the local autonomous cell.