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Updated: Jan 28, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
Published on: July 22, 2025
Smartphone-based multispectral imaging and machine-learning based analysis for discrimination between seborrheic
Sewoong Kim1, Jihun Kim1, Minjoo Hwang1
1Department of Information and Communication Engineering, Daegu Gyeongbuk Institute of Science & Technology, Daegu, 42988, South Korea.
Abstract:
For appropriate treatment, accurate discrimination between seborrheic dermatitis and psoriasis in a timely manner is crucial to avoid complications. However, when they occur on the scalp, differential diagnosis can be challenging using conventional dermascopes. Thus, we employed smartphone-based multispectral imaging and analysis to discriminate between them with high accuracy. A smartphone-based multispectral imaging system, suited for scalp disease diagnosis, was redesigned. We compared the outcomes obtained using machine learning-based and conventional spectral classification methods to achieve better discrimination. The results demonstrated that smartphone-based multispectral imaging and analysis has great potential for discriminating between these diseases.
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