人工智能和神经外科:跟踪血管内干预的抗血小板反应模式
Khushi Saigal1, Anmol Bharat Patel2, Brandon Lucke-Wold3
1College of Medicine, University of Florida, Gainesville, FL 32610, USA.
Medicina (Kaunas, Lithuania)
|October 28, 2023
概括
在神经外科手术中进行抗血小板治疗的管理是具有挑战性的,原因是出血与血栓形成的风险. 人工智能 (AI) 为优化抗血小板治疗方案和患者的治疗结果提供了潜在的解决方案.
科学领域:
- 神经外科 神经外科
- 心血管医学 心血管医学
- 人工智能的人工智能
背景情况:
- 血小板对于静血和血栓形成至关重要.
- 抗血小板治疗对于预防心血管事件至关重要.
- 神经外科对抗血小板治疗的管理提出了独特的挑战.
研究的目的:
- 对神经外科手术中抗血小板治疗的当前指导方针进行审查.
- 探索像PRU和TEG这样的抗血小板疗效监测方法.
- 调查人工智能在优化抗血小板治疗决策和神经外科患者坚持治疗方面的潜力.
主要方法:
- 对临床指导方针和支持的抗血小板治疗方案的审查.
- 探索P2Y12反应单元 (PRU) 和血栓凝结素学 (TEG) 监测.
- 对AI预测模型进行分析,以预测缺血和出血事件.
- 考虑人工智能来改善患者的坚持.
主要成果:
- 目前关于神经外科抗血小板治疗的指南是有限的.
- 在评估抗血小板反应方面,PRU和TEG监测存在局限性.
- 人工智能模型在预测不良结果和帮助治疗决策方面表现有希望.
- 人工智能有可能提高患者对抗血小板治疗方案的坚持.
结论:
- 在神经外科手术中优化抗血小板治疗需要仔细评估风险和益处.
- 人工智能具有个性化抗血小板治疗策略的巨大潜力.
- 对人工智能应用的进一步研究可以改善神经外科环境中的患者安全和结果.
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