AI Cervical Screening Camera for Low-Connectivity Diagnosis
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Solution Overview
Problem
Existing cervical cancer screening methods, particularly those using cytology and human observation, suffer from high false negative rates and are not suitable for medically underdeveloped areas due to reliance on internet connectivity and human subjectivity.
Innovation Solution
An AI-based cervical cancer screening system with a cervical cancer diagnosis camera device equipped with a pre-trained first read model for on-device image analysis, and a server with a second read model for remote specialist review, utilizing local and central servers for efficient reporting even in areas with slow internet connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cytology method is used for cervical cancer screening, then the screening can be performed, but the false negative rate is high due to low sensitivity
Solution Approach 1:
The patent replaces the manual cytology examination method with an automated AI-based image analysis system. The mechanical process of manual cell examination is substituted with computational algorithms that automatically analyze cervical cell images, thereby improving sensitivity and reducing false negative rates while maintaining screening capability.
Solution Approach 2:
The patent introduces an AI-based image analysis system as an intermediary between the cervical sample collection and the final diagnosis. This intermediary system processes images of cervical cells to provide objective, quantitative analysis that supplements traditional cytology methods, improving overall screening accuracy.
2Reliability
If human observation method is used to diagnose cervical images, then morphological abnormalities can be detected, but the diagnosis is subjective and not immediate
Solution Approach 1:
The patent replaces subjective human visual observation with automated AI-based image analysis. The mechanical process of manual image interpretation is substituted with computational algorithms that objectively analyze cervical images, eliminating subjectivity and providing immediate results without human variability.
Solution Approach 2:
The patent enables the system to perform self-diagnosis through automated AI analysis. The image analysis system independently processes and interprets cervical images without requiring human intervention, providing immediate, objective results while maintaining the ability to detect morphological abnormalities.
3Measurement precision
If AI-based reading system is implemented, then reading accuracy can be increased, but the system is not effectively used in medically underdeveloped areas
Solution Approach 1:
The patent divides the AI-based screening system into modular components that can be deployed in different settings. The system is segmented into image capture, AI analysis, and result reporting modules, allowing flexible deployment in medically underdeveloped areas where full infrastructure may not be available, while maintaining high reading accuracy through the core AI analysis component.
4Reliability
If remote reading request system is implemented, then reading specialists can be consulted, but the process requires internet connectivity which may be poor in some areas
Solution Approach 1:
The patent performs preliminary AI-based image analysis locally before requiring remote specialist review. By pre-processing images with AI algorithms and preparing preliminary results, the system reduces the need for extensive internet connectivity during the actual consultation, as specialists receive pre-analyzed cases rather than raw images requiring real-time processing.
Data Source
AI summary
According to an artificial-intelligence-based cervical cancer screening service system presented in the present invention, a first readout model pre-trained to read cervical images is loaded in a cervical cancer diagnosis camera device so that AI readout results are checked by only the cervical cancer diagnosis camera device even in an area where the Internet environment is poor, and thus help can be provided to cervical cancer screening.