AI Disease Classification Using Auscultation Position Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current disease diagnosis services using auscultation sound data are limited by their accuracy, as they do not effectively incorporate auscultation position data and biometric information, leading to suboptimal disease classification.
Innovation Solution
An electronic apparatus and method that trains an AI model using combined auscultation sound data, auscultation position data, and biometric data to generate feature information, which is then used to identify disease information with higher accuracy by concatenating or adding these data types, allowing for precise disease classification based on specific body parts or species.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only auscultation sound data is used for disease diagnosis, then the system complexity is low, but the disease classification accuracy is insufficient
Solution Approach 1:
The patent combines multiple data types (auscultation sound data, auscultation position data, and biometric data) into a unified input for the AI model. This merging of diverse data sources enhances disease classification accuracy by providing comprehensive diagnostic information while managing system complexity through integrated processing architecture.
Solution Approach 2:
The patent creates a composite data structure that integrates auscultation sound data, auscultation position data, and biometric data. This composite approach allows the AI model to process multiple information types simultaneously, improving diagnostic precision without requiring separate analysis systems for each data type.
2Measurement precision
If auscultation position data and biometric data are integrated with auscultation sound data, then disease diagnosis precision is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct modules: auscultation sound data processing, auscultation position data processing, and biometric data processing. Each module handles specific data types independently before integrating results, which reduces overall processing complexity while maintaining comprehensive analysis for improved diagnostic precision.
Solution Approach 2:
The patent introduces an intermediary AI model that receives processed data from multiple sources and integrates them into unified diagnostic conclusions. This intermediary component manages the complexity of integrating diverse data types by providing a centralized processing interface, thereby improving disease diagnosis precision without proportionally increasing system complexity.
Data Source
AI summary
Provided is a method for classifying diseases using artificial intelligence (AI) of an electronic apparatus. The method for classifying diseases may comprise obtaining auscultation sound data and auscultation position data, obtaining feature information based on the auscultation sound data and obtaining auscultation position information based on the auscultation position data, generating combined information by combining the feature information and the auscultation position information, and identifying at least one of disease information corresponding to the combined information, by using an AI model.