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人工智能在脓毒症/脓毒症休克诊断中的应用

Implications of using artificial intelligence in the diagnosis of sepsis/sepsis shock.

作者信息

Gorecki Gabriel-Petre, Tomescu Dana-Rodica, Pleș Liana, Panaitescu Anca-Maria, Dragosloveanu Șerban, Scheau Cristian, Sima Romina-Marina, Coman Ionuț-Simion, Grigorean Valentin-Titus, Cochior Daniel

机构信息

MD, PhD, Lecturer, Department of Anesthesia and Intensive Care, "Titu Maiorescu" University, Faculty of Medicine, 67A Gheorghe Petrașcu Street, 031593, Bucharest, Romania, and CF2 Clinical Hospital, Department of Anesthesia and Intensive Care, 63 Mărăşti Boulevard, 011464, Bucharest, Romania.

MD, PhD, Prof. Habil, Department of Anesthesia and Intensive Care, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021, Bucharest, Romania, and Fundeni Clinical Institute, Department of Anesthesia and Intensive Care, 258 Fundeni Road, 022328, Bucharest, Romania.

出版信息

Germs. 2024 Mar 31;14(1):77-84. doi: 10.18683/germs.2024.1419. eCollection 2024 Mar.

Abstract

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.

摘要

引言

脓毒症和脓毒性休克是严重的病理状态,其特征为机体对感染的全身性反应,可导致器官功能障碍和高死亡率。早期诊断和快速干预对于提高生存几率至关重要。然而,由于脓毒症症状不具特异性且患者对感染的反应存在差异,其诊断较为复杂。

方法

本研究的目的是分析使用人工智能(AI)诊断脓毒症和脓毒性休克的意义。用于分析使用人工智能(AI)诊断脓毒症和脓毒性休克意义的研究方法是文献综述。

结果

在使用人工智能诊断脓毒症的益处中,注意到人工智能可以快速分析大量临床数据以识别脓毒症的早期迹象,有时甚至在医护人员察觉症状之前。人工智能模型可以使用预测算法评估患者发生脓毒症的风险,从而实现可挽救生命的早期干预。人工智能有助于制定个性化治疗方案,根据每位患者的病史和对治疗的反应适应其特定需求。利用患者数据训练人工智能模型引发了对数据隐私和安全的担忧。

结论

人工智能有潜力彻底改变脓毒症的诊断和治疗方式,为早期识别和管理这一危急病症提供强大工具。然而,要实现这一潜力,研究人员、临床医生和技术开发者之间需要密切合作,同时还要应对伦理和实施方面的挑战。

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