Intelligent Wound Care Recommendation System
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Solution Overview
Problem
Chronic wounds pose a challenge due to the complexity of selecting appropriate medical appliances, such as dressings, as healthcare professionals face a vast array of options with varying information, making it difficult to accurately choose the right treatment.
Innovation Solution
A data processing system and method that utilizes multiple databases and processing engines to analyze wound symptom records, extract featured text information, and generate correlation weight values to recommend suitable medical appliances based on wound states and trends, facilitating the selection of appropriate treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional wound care practitioners manually select dressings from 3000+ items, then treatment accuracy may be maintained through expert knowledge, but the complexity of selection and time required increase significantly
Solution Approach 1:
The patent introduces an intelligent data processing system as an intermediary between the practitioner and the 3000+ dressing items. The system processes wound state data, analyzes product information, and generates recommended dressing selections, thereby reducing the complexity of manual selection while maintaining accuracy through automated analysis.
Solution Approach 2:
The patent replaces the manual mechanical selection process with an automated intelligent data processing system. The system automatically analyzes wound characteristics, compares them against product databases, and generates recommendations, substituting human manual browsing and selection with automated computational processes.
2Adaptability or versatility
If the number of dressing items increases to 3000+ varieties, then the adaptability to treat different wound states improves, but the difficulty of detecting and measuring the right dressing increases
Solution Approach 1:
The intelligent data processing system acts as an intermediary that manages the complexity of 3000+ dressing varieties. It processes wound state information, analyzes product characteristics, and filters appropriate options, making the large variety of dressings manageable and selectable based on specific wound requirements.
Solution Approach 2:
The patent creates a virtual representation of the dressing selection process through database storage and computational analysis. Instead of physically examining 3000+ products, the system uses digital copies of product information and wound data to simulate and determine the optimal selection.
3Loss of information
If comprehensive product information is stored for all dressings, then the completeness of treatment information improves, but the amount of information to be processed and analyzed increases
Solution Approach 1:
The patent extracts only the relevant featured text information from comprehensive product data using natural language processing. Instead of processing all available information, the system identifies and extracts key characteristics necessary for matching wound states with appropriate dressings, reducing processing time while maintaining information quality.
Solution Approach 2:
The patent replaces manual information processing with automated natural language processing and data analysis algorithms. The system automatically parses, analyzes, and compares product information against wound states, substituting time-consuming manual review with computational processing.
Data Source
AI summary
A data processing method includes the following steps. According to a wound symptom record, a trend of each wound state is analyzed. According to product data of the medical appliances in the treatment record, featured text information are extracted. First correlation weight values and second correlation weight values of the wound states are generated, the first correlation weight values indicate correlations between the wound states and the medical appliances, and the second correlation weight values indicate correlations between the wound states and the featured text information. A query condition is generated according to a target state, and a target nursing keyword is generated according to the query condition. Recommended medical appliances are selected from the medical appliances according to the target nursing keyword and the second correlation weight values.