Healthcare Object Recognition and Routing for Autonomous Data Discrimination
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Solution Overview
Problem
Existing healthcare systems lack the ability to autonomously determine if raw data collected is healthcare-related, relying solely on a priori human knowledge, and fail to discriminate between generic or ambient data that might or might not be medically relevant.
Innovation Solution
An HCO discrimination system with a sensor interface and recognition platform that analyzes digital representations of real-world scenes to identify and discriminate healthcare objects (HCOs) using discriminator characteristics, processes these objects through an HCO processor, and routes them to appropriate destinations based on routing rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing healthcare systems collect and incorporate raw data into medical records, then data assimilation is performed, but the systems cannot autonomously determine if the raw data is healthcare-related and rely on a priori human knowledge
Solution Approach 1:
The patent introduces an intermediary object recognition platform that acts as a mediator between raw data collection and medical record incorporation. This platform uses machine learning models to analyze sensor data and determine whether objects in the scene are healthcare-related, thereby automating the classification process while maintaining accuracy in medical relevance determination.
2Extent of automation
If healthcare systems rely on a priori human knowledge to determine healthcare data, then data classification is performed, but the systems lack the ability to autonomously discriminate between generic and medically relevant data
Solution Approach 1:
The system employs self-service mechanisms where the object recognition platform autonomously analyzes sensor data, identifies objects in real-world scenes, and determines their healthcare relevance without requiring continuous human intervention. The machine learning models are trained to independently discriminate between generic and medically relevant data, enabling automated decision-making while maintaining precision.
3Productivity
If real-time recognition and routing of healthcare objects is implemented, then data processing efficiency is enhanced, but system complexity increases
Solution Approach 1:
The patent segments the healthcare data processing system into distinct functional modules: sensor interfaces for data collection, an object recognition platform for analysis, machine learning models for classification, and routing mechanisms for data distribution. This segmentation allows real-time processing through specialized components while managing overall system complexity by distributing functions across modular units.
Data Source
AI summary
Healthcare object (HCO) discriminator systems and methods are presented. Systems can obtain a digital representation of a scene via a sensor interface. An HCO discriminator platform analyzes the digital representation to discriminate objects within the scene as being associated with a type of HCO or as being unrelated to a type of HCO. Once the HCO recognition platform determines that a type of HCO is relevant, it instantiates an actual HCO. The HCO can be routed to one or more destinations based on routing rules generated from a template or based on the manner in which the objects in the scene were discriminated.