Surgery Data Feature Extraction for Workflow Protocol Editing
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Solution Overview
Problem
Health workers face significant inconvenience when attempting to reuse surgery data, requiring extensive manual effort to reproduce and edit data for creating workflow protocols, due to the complexity of managing and analyzing various data types generated during surgical procedures.
Innovation Solution
A medical information processing apparatus and method that selects target data based on patient attributes, surgical procedure types, and disease types, extracts relevant features, particularly medical images, and edits these features to streamline data usage, utilizing a system that includes a selection unit, extraction unit, and editing processing unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If health workers manually reproduce and edit surgery data to create workflow protocols, then data accuracy and customization are improved, but work time and operational complexity increase significantly
Solution Approach 1:
The system automatically performs data reproduction, feature extraction, and compilation of surgery data and medical illustration images before the health worker needs to use them. The extraction unit pre-processes the surgery data to identify and extract relevant features, and the editing processing unit pre-compiles the workflow materials, so that when the health worker needs the data, it is already prepared and organized for immediate use.
Solution Approach 2:
The system enables self-service by automatically selecting target data based on selection conditions, extracting features from the data, and compiling workflow protocols without requiring health workers to manually reproduce or edit the data. The extraction unit autonomously identifies relevant features from surgery data, and the editing processing unit automatically creates the workflow materials, eliminating the need for manual intervention while maintaining data accuracy.
2Manufacturing precision
If health workers manually process and compile surgery data, then data quality and workflow customization are improved, but operational complexity and workload increase
Solution Approach 1:
The system performs self-service by automatically selecting target data according to predefined selection conditions, extracting relevant features through the extraction unit, and compiling workflow protocols through the editing processing unit. This automation eliminates the need for health workers to manually process and compile data, significantly reducing operational complexity while maintaining high data quality through systematic automated processing.
Solution Approach 2:
The patent replaces the manual mechanical process of data processing and compilation with an automated information processing system. The extraction unit and editing processing unit substitute for the health worker's manual operations, automatically performing feature extraction, data selection, and workflow compilation, thereby reducing operational complexity while preserving data quality through consistent automated procedures.
3Loss of information
If comprehensive surgery data is collected and managed, then data completeness and analysis accuracy are improved, but data management complexity and processing time increase
Solution Approach 1:
The extraction unit extracts only the relevant features from the comprehensive surgery data based on predefined selection conditions. Instead of managing and processing all raw surgery data, the system identifies and extracts specific feature data that is relevant to workflow protocol creation, thereby maintaining data completeness for analysis while significantly reducing data management complexity by working only with the extracted feature subset.
Solution Approach 2:
The system segments the comprehensive surgery data into manageable components by dividing it into target data selected according to specific conditions and feature data extracted from those targets. This segmentation allows the system to handle large volumes of comprehensive data without overwhelming complexity, processing only the relevant segments needed for workflow protocol creation while preserving access to the complete data set when necessary.
Data Source
AI summary
The present disclosure provides a medical information processing apparatus that comprises: a selection unit that selects, from among candidate data including surgery data acquired during surgery, target data corresponding to selection conditions that include a condition relating to a patient attribute, a condition relating to a surgical-procedure type, and a condition relating to a disease type; an extraction unit that detects a feature from the selected target data and extracts, from the target data, feature data corresponding to the detected feature; and an editing processing unit that edits the extracted feature data, wherein the extraction unit extracts at least a medical image as the feature data.