IEEE J Biomed Health Inform. 2019 Sep;23(5):2063-2079. doi: 10.1109/JBHI.2018.2879381. Epub 2018 Dec 25.
Precision medicine promises better healthcare delivery by improving clinical practice. Using evidence-based substratification of patients, the objective is to achieve better prognosis, diagnosis, and treatment that will transform existing clinical pathways toward optimizing care for the specific needs of each patient. The wealth of today's healthcare data, often characterized as big data, provides invaluable resources toward new knowledge discovery that has the potential to advance precision medicine. The latter requires interdisciplinary efforts that will capitalize the information, know-how, and medical data of newly formed groups fusing different backgrounds and expertise. The objective of this paper is to provide insights with respect to the state-of-the-art research in precision medicine. More specifically, our goal is to highlight the fundamental challenges in emerging fields of radiomics and radiogenomics by reviewing the case studies of Cancer and Alzheimer's disease, describe the computational challenges from a big data analytics perspective, and discuss standardization and open data initiatives that will facilitate the adoption of precision medicine methods and practices.
精准医学通过改善临床实践来承诺提供更好的医疗服务。利用基于证据的患者细分，其目的是实现更好的预后、诊断和治疗，从而改变现有的临床路径，以优化每个患者的特定需求的护理。当今医疗保健数据的丰富性，通常被描述为大数据，为新的知识发现提供了宝贵的资源，这有可能推进精准医学。后者需要跨学科的努力，以利用新形成的融合不同背景和专业知识的团体的信息、技术诀窍和医学数据。本文的目的是提供有关精准医学最新研究的见解。更具体地说，我们的目标是通过回顾癌症和阿尔茨海默病的案例研究，突出放射组学和放射基因组学等新兴领域的基本挑战，从大数据分析的角度描述计算挑战，并讨论将有助于采用精准医学方法和实践的标准化和开放数据计划。
