Avatar Annotating Medical Information From Blockchain
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Solution Overview
Problem
Managing medical information stored on a blockchain can be challenging due to difficulties in accessing and viewing it in an understandable format for medical practitioners, making it hard to efficiently retrieve and utilize this information.
Innovation Solution
A computer-implemented method that annotates an avatar representative of a human body with medical information using machine learning algorithms to associate and display the information securely and efficiently, allowing for automated access and intuitive interrogation by medical professionals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If medical information is stored on a blockchain to ensure security and confidentiality, then data security is improved, but accessibility and ease of viewing the information deteriorates
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between the blockchain storage and the user interface. This intermediary retrieves data from the blockchain, processes it through machine learning algorithms to extract meaningful information, and presents it in an accessible format. The intermediary layer maintains security by not exposing the underlying blockchain structure while enabling easy access to processed information.
Solution Approach 2:
The system creates processed copies of the medical information stored on the blockchain. Instead of requiring users to directly access and interpret raw blockchain data, the system generates simplified representations and visualizations that convey the same medical information in an easily understandable format, thereby improving accessibility without compromising the original secure storage.
2Reliability
If medical information is stored in structured formats on blockchain, then data security is improved, but ease of viewing and understanding the information deteriorates
Solution Approach 1:
The system changes the parameter of information presentation by transforming structured blockchain data into visually intuitive formats. Machine learning algorithms analyze the structured data and generate visual representations such as graphs, charts, or annotated images that maintain the security of original storage while dramatically improving understandability for medical practitioners.
Solution Approach 2:
The patent replaces the mechanical approach of directly viewing raw structured data with an intelligent processing system. Machine learning algorithms automatically interpret and visualize the structured information, substituting manual data analysis with automated intelligent processing that enhances understandability while preserving data security.
3Ease of operation
If keyword-based search is used to access medical information, then accessibility is improved, but efficiency and accuracy of information retrieval deteriorates
Solution Approach 1:
The system implements self-service functionality where the machine learning algorithms automatically understand and retrieve relevant medical information without requiring users to formulate precise keyword searches. The system autonomously interprets user needs and retrieves appropriate data, improving both accessibility and retrieval efficiency simultaneously.
Solution Approach 2:
The system incorporates feedback mechanisms where the machine learning models continuously learn from user interactions and retrieval patterns. This feedback loop enables the system to improve its information retrieval accuracy over time, making it increasingly efficient at understanding user needs and providing relevant medical information without relying on traditional keyword-based approaches.
Data Source
AI summary
There is provided a computer-implemented method of annotating an avatar representative of a human body with medical information associated with a patient, the method performed by a computer including a hardware processor, the method comprising: providing, by the hardware processor, the avatar; retrieving, by the hardware processor, electronic data from a blockchain, the electronic data describing the medical information; applying the electronic data, by the hardware processor, to one or more machine learning algorithms trained to associate the medical information with a body part from amongst a plurality of body parts of the human body; and annotating, by the hardware processor, the avatar with the medical information at a location of the associated body part.