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arXiv Open Access 2018

Semi-supervised Rare Disease Detection Using Generative Adversarial Network

Wenyuan Li Yunlong Wang Yong Cai Corey Arnold Emily Zhao +1 lainnya
Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

cs.LG stat.ML

Penulis (6)

W

Wenyuan Li

Y

Yunlong Wang

Y

Yong Cai

C

Corey Arnold

E

Emily Zhao

Y

Yilian Yuan

Format Sitasi

APA MLA BibTeX
Li, W., Wang, Y., Cai, Y., Arnold, C., Zhao, E., Yuan, Y. (2018). Semi-supervised Rare Disease Detection Using Generative Adversarial Network. https://arxiv.org/abs/1812.00547

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2018
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓