AI Nail Image Scoring for Reproducible Psoriasis Severity
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Solution Overview
Problem
Nail psoriasis, a common manifestation of psoriasis affecting up to 80% of individuals, is poorly understood and often undertreated due to a lack of effective diagnostic tools for quantifying disease severity, leading to inadequate treatment protocols.
Innovation Solution
A compute system with a nail ailment diagnostic mechanism using artificial intelligence (AI) to identify nails in images, segment individual nail images, evaluate severity, and generate AI-NAPSI and AI-NAPSOSI scores for accurate and reproducible nail psoriasis assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual assessment methods are used for nail psoriasis, then the diagnostic process is simple and easy to operation, but the measurement precision and reliability of disease severity quantification are insufficient
Solution Approach 1:
The patent replaces manual visual assessment with an artificial intelligence-based image analysis system. The AI model automatically processes nail images to generate standardized severity scores, substituting the mechanical/manual assessment process with an automated computational system that provides consistent and precise quantification of nail psoriasis severity.
Solution Approach 2:
The diagnostic system enables self-assessment capability through automated image analysis. The AI model independently evaluates nail images and generates diagnostic scores without requiring expert manual intervention, allowing the system to serve itself in the diagnostic process while maintaining high measurement precision.
2Reliability
If standardized quantification of nail psoriasis is implemented, then the reliability and reproducibility of diagnosis are improved, but the ease of operation and accessibility for clinical practice may be reduced
Solution Approach 1:
The system performs preliminary automated analysis of nail images before clinical decision-making. By pre-processing images and generating standardized severity scores automatically, the system prepares diagnostic information in advance, ensuring reliability while maintaining ease of operation during actual clinical use.
Solution Approach 2:
The AI-based image analysis system acts as an intermediary between raw nail images and clinical diagnosis. It translates visual nail characteristics into standardized quantitative scores that bridge the gap between visual assessment and objective measurement, improving reliability without complicating the clinical workflow.
3Productivity
If AI-based automated scoring is used, then the productivity and efficiency of diagnostic assessment are improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent replaces time-consuming manual assessment with automated AI-based image analysis. The system efficiently processes multiple nail images and generates standardized severity scores automatically, significantly improving diagnostic productivity while managing computational complexity through optimized algorithms.
Data Source
AI summary
A method of operation of a compute system includes: identifying a nail in a usable image; separating an individual nail image from the usable image by segmenting the usable image; evaluating an individual nail score by identifying severity of nail ailments in an entirety of the individual nail image; and generating an artificial intelligence (AI)-NAPSI score and an AI-NAPSOSI score based the individual nail score for displaying on a device.