Development of an Image Analysis-Based Prognosis Score Using Google's Teachable Machine in Melanoma.

ABSTRACT:

Background

The increasing number of melanoma patients makes it necessary to establish new strategies for prognosis assessment to ensure follow-up care. Deep-learning-based image analysis of primary melanoma could be a future component of risk stratification.

Objectives

To develop a risk score for overall survival based on image analysis through artificial intelligence (AI) and validate it in a test cohort.

Methods

Hematoxylin and eosin (H&E) stained sections of 831 melanomas, diagnosed from 2012-2015 were photographed and used to perform deep-learning-based group classification. For this purpose, the freely available software of Google's teachable machine was used. Five hundred patient sections were used as the training cohort, and 331 sections served as the test coho

SUBMITTER: Forchhammer S 

PROVIDER: S-EPMC9105888 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature