AI Health Platform Document Automation
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Solution Overview
Problem
Current health platforms require manual user intervention for document upload and management, which is time-consuming and inefficient, especially after medical appointments, as users need to obtain and upload physical copies of documents.
Innovation Solution
An automated system utilizing a machine learning module for optical recognition and data extraction in health documents, allowing for automated linking and storage of documents to user profiles via email, SMS, or messaging services, eliminating the need for users to manually upload documents and enabling classification and notification of new health documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual user upload is implemented, then document management is achieved, but user time consumption increases and automation is reduced
Solution Approach 1:
The system enables self-service by automatically extracting user identification from incoming messages and autonomously uploading documents to the correct user profiles without requiring user intervention. The machine learning model performs automatic document classification and routing, allowing the system to serve itself rather than requiring manual user action.
Solution Approach 2:
The system performs preliminary action by pre-processing documents through optical recognition and data extraction before they need to be accessed. Documents are automatically classified, user identification is extracted in advance, and documents are pre-uploaded to the appropriate profiles, so that when users need their documents, they are already organized and available.
2Ease of operation
If manual document upload by users is required, then document security is maintained, but ease of operation deteriorates
Solution Approach 1:
The system introduces an intermediary machine learning model that acts as a mediator between incoming documents and user profiles. This intermediary automatically extracts user identification, classifies documents, and routes them to the correct profiles, simplifying the user experience while managing the underlying complexity through automated intermediate processing steps.
Solution Approach 2:
The system replaces the mechanical manual upload process with automated optical recognition and machine learning-based data extraction. Instead of users physically uploading documents through interfaces, the system uses automated image processing and pattern recognition to extract information and perform uploads, substituting mechanical user actions with automated computational processes.
3Productivity
If users must obtain physical copies of documents, then document authenticity is ensured, but productivity decreases
Solution Approach 1:
The system uses optical recognition to create digital copies of physical or image-based documents. The machine learning model extracts text and data from these copies, automatically processes them, and stores them in the database, eliminating the need for users to physically handle, scan, or manually re-enter document information while maintaining document integrity through automated verification.
Data Source
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AI summary
An automated system (1) for managing an artificial intelligence health platform comprising: ➢ a first data storage system (11) storing o a plurality of user identification elements, each user identification element being associated with a user among a plurality of users, o for each user, at least one health document linked to said user identification element, ➢ a server (10) configured to communicate with said first data storage system (11), said server being configured to: o receive a message with an attached file, said attached file being an attached health document, o implement an artificial intelligence module (101) implementing a machine learning model, said machine learning model being configured to perform optical recognition and data extraction in the attached health document, said extracted data being a user identification element, record and link said health document to the corresponding user in the first data storage system (11) on the basis of the extracted personal identification element