Genomic sequencing to aid diagnosis in pediatric and prenatal practice: Examining clinical utility, ethical implications, payer coverage, and data integration in a diverse population.

基因组测序有助于儿科和产前实践中的诊断：检查不同人群的临床效用、伦理影响、付款人覆盖范围和数据整合。

• 批准号: 9929780
• 负责人: Pui-Yan KWOK
• 金额: $ 16.7万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-04 至 2021-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9929780
• 关键词: Artificial Intelligence; Big Data; Biosensor; Childhood; Clinical; Data Analyses; Data Science; Detection; Diagnosis; Economics; Electronic Health Record; Ethics; Future; Genetic screening method; Genomic medicine; Genomics; Goals; Health; Healthcare; Intervention; Machine Learning; Patients; Population Heterogeneity; Precision Health; Provider; Societies; Source; Sum; Work; data integration; disorder prevention; experience; formal learning; genetic information; informal learning; precision medicine; prenatal

PROJECT SUMMARY I propose to gain experience in what are becoming the next big topics in genomic medicine – the integration of “big data” using data science in order to achieve “precision health” – what could be summed up as “data science of the future”. These topics emerge from - but go beyond - the narrower concept of “precision medicine” as the use of genetic information for treatment decisions. The goal is to develop experience in data science and precision health so that my work can serve as a bridge between my field of economics and these fields - and begin to prepare for the future challenges as they emerge.

项目摘要 我建议在基因组医学的下一个大课题--整合 “大数据”利用数据科学，以实现“精准健康”-什么可以概括为“数据 未来的科学”。这些主题源于--但又超越--狭义的“精确”概念 医学”作为使用遗传信息的治疗决策。目标是开发数据方面的经验 科学和精确健康，使我的工作可以作为我的经济学领域和这些领域之间的桥梁， 领域-并开始准备迎接未来出现的挑战。