利用人工智能更好地预测和开发生物标志物。

Using Artificial Intelligence to Better Predict and Develop Biomarkers.

机构信息

Georgetown University School of Medicine, Washington, DC, USA.

Department of Medicine, Division of Cardiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Department of Medicine, Division of Cardiology, Harvard Medical School, Boston, MA, USA; Baim Institute for Clinical Research, Boston, MA, USA.

出版信息

Clin Lab Med. 2023 Mar;43(1):99-114. doi: 10.1016/j.cll.2022.09.021.

DOI:10.1016/j.cll.2022.09.021

PMID:36764811

Abstract

Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, transcripts, proteins, and metabolites. Furthermore, improvements in artificial intelligence (AI) have made the interpretation of large omics data sets easier and improved analysis. Use of omics and AI in biomarker discovery can aid clinicians by identifying markers of risk for developing HF, monitoring care, determining prognosis, and developing druggable targets. Combined, AI has the power to improve HF patient care.

摘要

技术的进步提高了心力衰竭（HF）领域的生物标志物发现。通过使用高通量组学平台在基因、转录本、蛋白质和代谢物水平上表现出 HF，曾经是一个缓慢而费力的过程，现在已经提高了效率。此外，人工智能（AI）的改进使得对大型组学数据集的解释变得更加容易，并提高了分析能力。在生物标志物发现中使用组学和 AI 可以通过识别发生 HF 的风险标志物、监测护理、确定预后和开发可药物靶向来帮助临床医生。AI 具有结合起来改善 HF 患者护理的力量。