Self-Diagnosis Server Module for Medical Information
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Solution Overview
Problem
Current medical information applications primarily provide location-based services for hospitals and pharmacies but lack the ability to offer self-diagnosis capabilities, limiting users' ability to receive personalized medical insights and efficient hospital selection based on their symptoms.
Innovation Solution
A diagnostic apparatus and server system that allows users to input queries related to body parts, generating a diagnosis result by analyzing their answers, which can then be used to identify potential diseases and recommend suitable hospitals, while also providing medical teams with preliminary examination data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If medical information applications provide only location-based services for hospitals and pharmacies, then the application structure remains simple and easy to operate, but the application cannot offer self-diagnosis capabilities or personalized medical insights
Solution Approach 1:
The application is divided into distinct functional modules: a body part selection interface, a query extraction module, an answer analysis engine, and a hospital recommendation system. Each module handles a specific aspect of the self-diagnosis process, allowing the system to gain advanced functionality while maintaining manageable complexity through modular architecture
Solution Approach 2:
The medical information providing server serves multiple functions: it stores hospital location information, maintains disease query databases, processes user answers, generates diagnosis results, and provides hospital recommendations. This multi-functional design allows the system to offer self-diagnosis capabilities without requiring separate specialized systems for each function
2Ease of operation
If the application displays hospitals by location only, then the information presentation remains simple, but users cannot efficiently select hospitals based on their specific symptoms or diagnosed conditions
Solution Approach 1:
The system implements a feedback mechanism where user answers to health-related queries are processed to generate diagnosis results, which then feed into the hospital recommendation engine. This closed-loop feedback allows the system to continuously refine hospital recommendations based on the user's specific symptoms and conditions, transforming static location information into dynamic, personalized medical guidance
Solution Approach 2:
The system performs preliminary diagnostic analysis by processing user answers to health queries before presenting hospital options. This preliminary action of generating diagnosis results in advance allows users to receive tailored hospital recommendations that are pre-matched to their specific medical needs, rather than requiring manual filtering of general hospital listings
Data Source
AI summary
The present disclosure includes an input module, a memory in which a self-diagnostic application is stored, and a processor configured to execute the self-diagnostic application. Herein, upon execution of the self-diagnostic application, the processor extracts multiple queries corresponding to a body part selected by a user on the basis of the user's input signal to select any one of multiple body parts and generates a diagnosis result for the user on the basis of the user's answers to the multiple queries. Further, the diagnosis result corresponds to at least one of multiple diseases.