使用人工智能诊断败血症/败血症休克的意义。

IF 1.7 Q3 INFECTIOUS DISEASES GERMS Pub Date : 2024-03-31 eCollection Date: 2024-03-01 DOI:10.18683/germs.2024.1419
Gabriel-Petre Gorecki, Dana-Rodica Tomescu, Liana Pleș, Anca-Maria Panaitescu, Șerban Dragosloveanu, Cristian Scheau, Romina-Marina Sima, Ionuț-Simion Coman, Valentin-Titus Grigorean, Daniel Cochior
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引用次数: 0

摘要

引言败血症和脓毒性休克是一种严重的病理状态,其特点是全身对感染的反应,可导致器官功能障碍和高死亡率。早期诊断和快速干预对提高存活率至关重要。然而,由于败血症的症状不具特异性,而且患者对感染的反应也各不相同,因此其诊断非常复杂:本研究的目的是分析在败血症和脓毒性休克诊断中使用人工智能(AI)的意义。在分析脓毒症和脓毒性休克诊断中使用人工智能(AI)的意义时采用的研究方法是文献综述:在脓毒症诊断中使用人工智能的好处中,人们注意到人工智能可以快速分析大量临床数据,识别脓毒症的早期征兆,有时甚至在医务人员发现症状之前。人工智能模型可以使用预测算法来评估病人患败血症的风险,从而进行早期干预,挽救生命。人工智能有助于制定个性化治疗计划,根据每位患者的病史和对治疗的反应来满足其特定需求。使用患者数据来训练人工智能模型会引发对数据隐私和安全的担忧:人工智能有可能彻底改变败血症的诊断和治疗,为早期识别和管理这种危重症提供强大的工具。然而,要实现这一潜力,研究人员、临床医生和技术开发人员之间必须密切合作,并解决伦理和实施方面的挑战。
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Implications of using artificial intelligence in the diagnosis of sepsis/sepsis shock.

Introduction: Sepsis and septic shock represent severe pathological states, characterized by the systemic response to infection, which can lead to organ dysfunction and high mortality. Early diagnosis and rapid intervention are crucial for improving survival chances. However, the diagnosis of sepsis is complex due to its nonspecific symptoms and the variability of patient responses to infections.

Methods: The objective of this research was to analyze the implications of using artificial intelligence (AI) in the diagnosis of sepsis and septic shock. The research method applied in the analysis of the implications of using artificial intelligence (AI) in the diagnosis of sepsis and septic shock is the literature review.

Results: Among the benefits of using AI in the diagnosis of sepsis, it is noted that artificial intelligence can rapidly analyze large volumes of clinical data to identify early signs of sepsis, sometimes even before symptoms become evident to medical staff. AI models can use predictive algorithms to assess the risk of sepsis in patients, allowing for early interventions that can save lives. AI can contribute to the development of personalized treatment plans, adapting to the specific needs of each patient based on their medical history and response to treatment. The use of patient data to train AI models raises concerns regarding data privacy and security.

Conclusions: Artificial intelligence has the potential to revolutionize the diagnosis and treatment of sepsis, offering powerful tools for early identification and management of this critical condition. However, to realize this potential, close collaboration between researchers, clinicians, and technology developers is necessary, as well as addressing ethical and implementation challenges.

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来源期刊
GERMS
GERMS INFECTIOUS DISEASES-
CiteScore
2.80
自引率
5.00%
发文量
36
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