Medical Condition Prediction System Using Data Correlation
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Solution Overview
Problem
Radiologists and physicians often lack comprehensive information about medical subjects, leading to incomplete diagnoses and missed opportunities for accurate prediction of medical conditions, as their assessments are limited to manual inspection of images and data without historical or genetic context.
Innovation Solution
A system and method that integrate medical information systems with electronic data systems to derive the probability of a medical condition by correlating diagnostic and demographic data with historical, genetic, and medical condition data from similar subjects, using a data processing unit to analyze patterns and provide predictive analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radiologists and physicians rely solely on manual inspection of images and data, then the diagnostic process remains simple and quick, but the diagnostic accuracy and completeness deteriorate due to lack of comprehensive historical and genetic information
Solution Approach 1:
The patent merges multiple independent information systems (PACS, EMR, genetic databases, research databases) into an integrated diagnostic system. The data processing unit correlates data from these separate sources to provide comprehensive diagnostic information, thereby improving diagnostic accuracy without requiring physicians to manually access multiple systems
Solution Approach 2:
The data processing unit acts as an intermediary that automatically correlates and integrates data from multiple information systems. It processes and synthesizes information from PACS, EMR, genetic databases, and research databases, presenting integrated results to physicians without requiring them to manually query each source
2Reliability
If additional information from electronic data systems is integrated, then the predictive capability and diagnostic completeness improve, but the information processing complexity and time requirements worsen
Solution Approach 1:
The system performs preliminary actions by pre-integrating and organizing data from multiple information systems before diagnostic queries are made. The data processing unit maintains pre-correlated data relationships and readily available integrations, so when a diagnostic query is made, the system can quickly retrieve and present relevant information without performing time-consuming data gathering and correlation at the moment of need
3Measurement precision
If comprehensive data from multiple information systems is correlated, then the probability prediction accuracy improves, but the data processing complexity and computational requirements worsen
Solution Approach 1:
The data processing unit serves as an intermediary that handles the complex task of correlating data from multiple information systems. It automatically performs the computationally intensive tasks of data integration, pattern recognition, and probability calculation, shielding physicians from this complexity while providing accurate probability predictions for medical conditions
Data Source
AI summary
In one embodiment, a method of deriving probability of a medical condition is provided. The method comprises obtaining a first medical data corresponding to a first medical subject from at least one medical information system, obtaining a second medical data corresponding to the first medical subject from an electronic data system, selecting at least one second medical subject with a second medical data substantially same as the second medical data of the first medical subject, obtaining medical condition data for the second medical subject, wherein the medical condition data includes data corresponding to a medical condition, correlating the first medical data with the medical condition data and deriving probability of the medical condition in the first medical subject based upon the first medical data and the medical condition data.