Can I read Knowledge-guided Meta Learning for Disease Prediction on EtoBox?

Knowledge-guided Meta Learning for Disease Prediction by Qiuling Suo; Hyun Jae Cho; Jingyuan Chou; Stefan Bekiranov; Chongzhi Zang; Aidong Zhang is a book available to read on EtoBox.

What is Knowledge-guided Meta Learning for Disease Prediction about?

Annotated data samples in real-world biomedical applications are often limited. However, many machine learning approaches rely primarily on training systems based on big labeled data corpora. For instance, deep learning systems must be shown many examples before they can classify things accurately. While deep learning has achieved great success in many fields, it can easily lead to overfitting issues when dealing with a small number of samples with high-dimensional features in a cohort. The Cancer Genome Atlas (TCGA) [1] is such an example, which characterizes the molecular profiles of over 20,000 cancer and normal samples with clinical outcomes spanning 33 cancer types. However, the number of patients for each cancer type is small (varying from 51 to 1098), which shows the scenario of many different domains (cancer types) with each domain having few samples. Transfer-learning has been proposed to re-use the trained model parameters in similar applications. However, transfer learning cannot be effectively applied from one domain to a different domain. More recently, meta learning, which utilizes prior knowledge learned from related tasks and generalizes to new tasks of limited supe

Author

Qiuling Suo; Hyun Jae Cho; Jingyuan Chou; Stefan Bekiranov; Chongzhi Zang; Aidong Zhang

Publisher

Elsevier

Published

2023

Language

EN