In vivo study to evaluate an intelligent algorithm for time efficient detection of malignant melanoma using dermatofluoroscopy

Published: 6 December 2024| Version 1 | DOI: 10.17632/cg6zjrsd79.1
Contributor:
Karl Weihmann

Description

This contains supplementary figures for "In vivo study to evaluate an intelligent algorithm for time efficient detection of malignant melanoma using dermatofluoroscopy" Contents: Supplementary Figure 1. “Color clusters“ Figure illustrating the color clusters for nCl=9 and their associated occurrence in melanoma (higher values mean that a color is found more often on melanoma than non-melanoma). Note that each color type may display a different level of class-separability. Supplementary Figure 2. “Boxplot comparing measurement points“ Boxplot comparing the number of measurement points of the conventional 200 µm grid method and the intelligent algorithm at nCl=9 and g=0.001 Supplementary Table I. “Comparison of diagnostic accuracy and measurement points“ Histopathological diagnosis compared to dermatofluoroscopic prediction (conventional and new) and data points needed. SSM: superficial spreading melanoma; Correct predictions, i.e., true positives and true negatives, are highlighted in green, while false positives are in pink and false negative in red.

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Institutions

Charite Universitatsmedizin Berlin

Categories

Artificial Intelligence, Dermatology, Melanoma, Nevus

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