Frey Lewis J
Department of Public Health Sciences, Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29425, USA.
Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson Veteran Affairs Medical Center, Charleston, SC 29401, USA.
Genes (Basel). 2018 Dec 28;10(1):18. doi: 10.3390/genes10010018.
The integration of phenotypes and genotypes is at an unprecedented level and offers new opportunities to establish deep phenotypes. There are a number of challenges to overcome, specifically, accelerated growth of data, data silos, incompleteness, inaccuracies, and heterogeneity within and across data sources. This perspective report discusses artificial intelligence (AI) approaches that hold promise in addressing these challenges by automating computable phenotypes and integrating them with genotypes. Collaborations between biomedical and AI researchers will be highlighted in order to describe initial successes with an eye toward the future.
表型与基因型的整合正处于前所未有的水平,并为建立深度表型提供了新机遇。有许多挑战需要克服,具体而言,数据加速增长、数据孤岛、不完整性、不准确以及数据源内部和之间的异质性。本观点报告讨论了人工智能(AI)方法,这些方法有望通过自动化可计算表型并将其与基因型整合来应对这些挑战。将重点介绍生物医学研究人员与人工智能研究人员之间的合作,以便着眼未来描述初步的成功案例。