Activity: Publication peer-review and editorial work (RGC: 61) › RGC 61 - Journal editor
Description
The rise of high-throughput assays (“-omics”), big data, and computational approaches offers promising means by which to dissect the etiology, improve the risk stratification, enhance the prediction, and promote the prevention of various diseases, particularly complex diseases. As generating large amounts of data becomes easier, maximizing their utility requires interdisciplinary teams that can ask the right questions, design the appropriate studies, and conduct the appropriate analyses.
This Special Issue will focus on the disciplines of computational biology, artificial intelligence, epidemiology, and clinical sciences, both separately and in combination. It aims to highlight how disease prediction and prevention can be advanced by leveraging the strengths of each of these fields.