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血栓性疾病的遗传因素、风险预测及人工智能应用

Genetic factors, risk prediction and AI application of thrombotic diseases.

作者信息

Wang Rong, Tang Liang V, Hu Yu

机构信息

Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Key Lab of Molecular Biological Targeted Therapies of the Ministry of Education, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Exp Hematol Oncol. 2024 Aug 27;13(1):89. doi: 10.1186/s40164-024-00555-x.

Abstract

In thrombotic diseases, coagulation, anticoagulation, and fibrinolysis are three key physiological processes that interact to maintain blood in an appropriate state within blood vessels. When these processes become imbalanced, such as excessive coagulation or reduced anticoagulant function, it can lead to the formation of blood clots. Genetic factors play a significant role in the onset of thrombotic diseases and exhibit regional and ethnic variations. The decision of whether to initiate prophylactic anticoagulant therapy is a matter that clinicians must carefully consider, leading to the development of various thrombotic risk assessment scales in clinical practice. Given the considerable heterogeneity in clinical diagnosis and treatment, researchers are exploring the application of artificial intelligence in medicine, including disease prediction, diagnosis, treatment, prevention, and patient management. This paper reviews the research progress on various genetic factors involved in thrombotic diseases, analyzes the advantages and disadvantages of commonly used thrombotic risk assessment scales and the characteristics of ideal scoring scales, and explores the application of artificial intelligence in the medical field, along with its future prospects.

摘要

在血栓性疾病中,凝血、抗凝和纤维蛋白溶解是三个关键的生理过程,它们相互作用以维持血管内血液处于适当状态。当这些过程失衡时,如凝血过度或抗凝功能降低,就会导致血栓形成。遗传因素在血栓性疾病的发病中起重要作用,并存在地区和种族差异。是否启动预防性抗凝治疗的决策是临床医生必须仔细考虑的问题,这导致了临床实践中各种血栓形成风险评估量表的发展。鉴于临床诊断和治疗存在相当大的异质性,研究人员正在探索人工智能在医学中的应用,包括疾病预测、诊断、治疗、预防和患者管理。本文综述了血栓性疾病相关各种遗传因素的研究进展,分析了常用血栓形成风险评估量表的优缺点以及理想评分量表的特点,并探讨了人工智能在医学领域的应用及其未来前景。

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