人工智能和机器学习在心血管成像和诊断中的作用
Setareh Reza-Soltani1, Laraib Fakhare Alam2, Omofolarin Debellotte3
1Advanced Diagnostic & Interventional Radiology Center (ADIR), Tehran University of Medical Sciences, Tehran, IRN.
人工智能 (AI) 和机器学习 (ML) 显示出改善心血管成像诊断和患者护理的巨大潜力. 解决数据,可解释性和整合方面的挑战是实现人工智能的关键.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 心血管疾病是全球死亡的主要原因之一.
- 准确和及时的诊断对于有效的心血管护理至关重要.
- 人工智能 (AI) 和机器学习 (ML) 为医学诊断提供了潜在的进步.
研究的目的:
- 审查AI和ML在心血管成像中的当前应用.
- 探索AI和ML在这个领域的未来潜力.
- 识别心脏病学AI实施的挑战和伦理考虑.
主要方法:
- 在心血管成像中AI和ML应用的叙述性审查.
- 讨论各种成像方式 (心声学,CT,MRI,核成像).
- 探索AI在诊断特定心血管疾病和预测事件中的作用.
主要成果:
- 人工智能显示出提高诊断准确性,效率和个性化心血管护理的潜力.
- 关键的应用领域包括冠状动脉疾病,门疾病,心肌病和心律不整.
- 仍然存在重大挑战,包括数据标准化,模型解释性,监管障碍和临床整合.
结论:
- 人工智能对彻底改变心血管成像和改善患者治疗结果具有重大前景.
- 解决数据质量,可解释性,监管和工作流集成方面的挑战至关重要.
- 临床医生,数据科学家和决策者之间的合作对于道德和有效的AI实施至关重要.
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