急性缺血性脑卒中(AIS)是一种严重影响人类健康相关的疾病,其拥有高发病率和高死亡率,并与吸烟、高脂饮食等不良生活习惯相关,人工智能(AI)比如机器学习(ML)和深度学习(DL),可以实现从临床及辅助检查尤其是成像学检查中提取特征数据,经过算法处理,得出可信结果。近几年AI更多地应用于医院系统的工作中,并成为临床工作及科研项目有力的帮手。本文全面综述了AI预测急性缺血性脑卒中(AIS)患者在经过血管内治疗,尤其是经过血栓切除术治疗后的预后情况,从而实现精准有效的临床管理和护理决策。此外,本文还批判性地评估了现有研究的局限性,并且指出了新的研究方向,最终目标是提高AIS患者的生存率。Acute ischemic stroke (AIS) is a serious human health-related disease that is characterized by elevated morbidity and mortality rates. It is often linked to detrimental lifestyle behaviors, including smoking and high-fat dietary intake. The advent of artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL) methodologies, facilitates the extraction and analysis of feature data derived from clinical and ancillary assessments, particularly imaging studies. These data are processed through sophisticated algorithms to yield reliable outcomes. In recent years, AI has been increasingly integrated into hospital systems, emerging as a formidable tool in both clinical practice and research initiatives. This paper presents a comprehensive analysis of AI applications in predicting the prognosis of acute ischemic stroke (AIS) patients following endovascular interventions, with a particular focus on thrombectomy procedures. The objective is to enhance the accuracy and efficacy of clinical management and care decision-making processes. Furthermore, the study critically examines the limitations inherent in current research and identifies prospective avenues for future investigation, ultimately aiming to improve the survival outcomes of AIS patients.
缺血性卒中是一种高致残率和致死率的脑血管疾病,早期治疗以溶栓和神经保护为主。神经保护剂可改善溶栓再通引发的缺血再灌注损伤,但因存在脑靶向性不足和作用靶点单一等缺陷,在临床应用中疗效欠佳。聚多巴胺纳米颗粒是一种具有自由基清除、多功能修饰、光热转换等特性的纳米材料,在神经保护、药物靶向、多靶点治疗方面具有独特优势,为突破目前神经保护治疗的局限提供了一个多功能集合平台。本文总结了聚多巴胺纳米颗粒的抗炎抗氧化的神经保护作用,系统阐述了聚多巴胺纳米颗粒通过各种途径促进神经保护剂靶向大脑,并结合其本身的自由基清除功能发挥多靶点治疗,为疗效确切的脑保护治疗方案的开发和应用提供新的策略。Ischemic stroke is a cerebrovascular disease with a high disabling and lethal rate, and early treatment is mainly thrombolysis and neuroprotection. Neuroprotective agents can improve ischemia-reperfusion injury caused by thrombolytic recanalization, but they have poor efficacy in clinical application due to shortcomings such as insufficient brain targeting and single target. Polydopamine nanoparticles are nanomaterials with the characteristics of free radical scavenging, multifunctional modification, photothermal conversion, etc., which have unique advantages in neuroprotection, drug targeting, and multi-target therapy, and provide a multifunctional platform for breaking through the limitations of current neuroprotective therapy. In this paper, we summarize the neuroprotective effects of polydopamine nanoparticles on anti-inflammatory and antioxidant effects, and systematically elaborate that polydopamine nanoparticles promote the targeting of neuroprotective agents to the brain through various pathways, and combine their own free radical scavenging functions to exert multi-target therapy, providing a new strategy for the development and application of brain protection therapy regimens with definite efficacy.
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