Automated Radiology Feedback System Using NLP
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Solution Overview
Problem
Radiologists face challenges in receiving timely and relevant feedback on their diagnoses due to the lack of standardized information sharing between radiology and pathology departments, leading to diagnostic errors and unnecessary biopsies.
Innovation Solution
An automated radiology feedback system that processes medical reports to identify relevant subsequent examinations, calculates similarity scores, and provides notifications to radiologists, using language processing and machine learning models to determine the relevance of reports and improve diagnosis accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual information sharing between radiology and pathology departments is used, then feedback can be provided to radiologists, but the process is time-consuming and prone to errors
Solution Approach 1:
The patent replaces manual information sharing (mechanical human processes) with an automated computer-based system that uses natural language processing and machine learning models to extract, match, and deliver feedback information between radiology and pathology departments, thereby reducing time and improving reliability
Solution Approach 2:
The system enables self-service by automatically processing medical reports, extracting relevant information, and providing feedback without requiring manual intervention from radiologists or pathologists, allowing the system to serve itself in identifying and delivering feedback opportunities
2Reliability
If comprehensive medical reports are analyzed to provide feedback, then diagnostic accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the complex task of analyzing comprehensive medical reports into distinct modules: document structure processing, syntactic parsing, entity extraction, anatomy inference, and similarity calculation. Each module handles a specific aspect of the analysis, making the overall system more manageable and maintainable while still processing comprehensive reports
Solution Approach 2:
The patent introduces intermediary components such as the processed report structure and the feedback opportunity identification model that mediate between the raw comprehensive medical reports and the final feedback delivery, simplifying the interaction between different system components
3Productivity
If automated processing of medical reports is implemented, then feedback efficiency increases, but information loss may occur during processing
Solution Approach 1:
The patent creates a processed report that is a structured copy of the original medical report, preserving all essential information while organizing it in a machine-readable format. This copying approach allows automated processing to proceed efficiently while maintaining the integrity of the original medical information for verification purposes
Data Source
AI summary
A method for providing feedback to a radiologist, including: receiving a plurality of medical reports; processing the plurality of medical reports to produce a processed report that extracts patient medical information; receiving a feedback request related to a radiology report; identifying a medical report related to the feedback request; and providing a to notification the radiologist regarding the identified medical report related to the feedback request.