深度学习在脓毒症诊断中的研究进展
Research Progress of Deep Learning in Diagnosis of Sepsis
DOI: 10.12677/jcpm.2024.34241, PDF,    科研立项经费支持
作者: 崔翔宇*：济宁医学院临床医学院，山东 济宁；谢学猛, 孙 强#：济宁医学院附属医院重症医学科，山东 济宁；高 泷：山东第一医科大学护理学院，山东 泰安
关键词: 深度学习；人工智能；脓毒症；Deep Learning； Artificial Intelligence； Sepsis
摘要: 脓毒症是一种高发病率、病死率的急危重综合征，早期诊断与治疗是改善其预后的关键。尽管现代医疗技术有了长足的进步，但脓毒症的及时而精准的诊断仍面临严峻挑战。近年来人工智能发展迅速，在医疗方面的应用日益广泛，在临床多种疾病的诊疗中成果颇丰。深度学习属于人工智能的前沿技术，可分析海量、高维的医疗数据，为脓毒症的诊断提供了一个新思路。本文总结了深度学习在脓毒症诊断中的研究进展，以期为脓毒症的诊疗提供参考。
Abstract: Sepsis is an acute and critical syndrome with high incidence rate and mortality. Early diagnosis and treatment is the key to improving its prognosis. Despite significant advances in modern medical technology, timely and accurate diagnosis of sepsis still faces serious challenges. In recent years, artificial intelligence has developed rapidly and its applications in healthcare have become increasingly widespread, with fruitful results in the diagnosis and treatment of various diseases in clinical practice. Deep learning is a cutting-edge technology in artificial intelligence that can analyze massive and high-dimensional medical data, providing a new approach for the diagnosis of sepsis. This article summarizes the research progress of deep learning in the diagnosis of sepsis, in order to provide reference for the diagnosis and treatment of sepsis.
文章引用：崔翔宇, 谢学猛, 高泷, 孙强. 深度学习在脓毒症诊断中的研究进展[J]. 临床个性化医学, 2024, 3(4): 1676-1681. https://doi.org/10.12677/jcpm.2024.34241

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