Semi-supervised Rare Disease Detection Using Generative Adversarial Network

作者：Wenyuan Li, Yunlong Wang, Yong Cai, Corey Arnold, Emily Zhao, Yilian Yuan · 发表于：arXiv (Cornell University) · 年份：2018 · DOI：10.48550/arxiv.1812.00547 · 被引用次数：17 · 研究领域：Artificial Intelligence in Healthcare、Machine Learning in Healthcare、COVID-19 diagnosis using AI

Rare diseases affect a relatively small number of people, which limits investment in research for treatments and cures. Developing an efficient method for rare disease detection is a crucial first step towards subsequent clinical research. In this paper, we present a semi-supervised learning framework for rare disease detection using generative adversarial networks. Our method takes advantage of the large amount of unlabeled data for disease detection and achieves the best results in terms of precision-recall score compared to baseline techniques.