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Antipsychotic drugs are a crucial treatment method for acute and chronic psychoses, bipolar illness, and behavioral disorders. The selection of these drugs depends on several factors, including the state of the disease, clinical judgment, possible drug interactions, and the patient's sensitivity to adverse effects. In immediate scenarios, such as delirium and dementia, short-term treatment with low doses of high-potency typical or atypical agents can effectively manage symptom exacerbation. For...

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适应性神经模糊推理系统指导目标函数参数优化,用于逆向治疗计划.

Eduardo Cisternas Jiménez1, Fang-Fang Yin1,2,3

  • 1Medical Physics Graduate Program, Duke University, Durham, NC, United States.

Frontiers in artificial intelligence
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PubMed
概括

本研究介绍了一种使用自适应神经模糊推理系统 (ANFIS) 的AI系统,用于自动化强度调制辐射治疗 (IMRT) 计划. ANFIS系统优化了治疗参数,显著提高了剂量递送的准确性,减少了健康组织的暴露.

关键词:
适应性神经模糊推理系统人工智能在放射治疗规划中的应用一个模糊的推断系统.模糊的集合理论 模糊的集合理论强度调节的辐射疗法.治疗计划参数 治疗计划参数治疗规划系统的系统规划

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科学领域:

  • 医学物理 医学物理
  • 人工智能在医学中的应用
  • 辐射瘤学 辐射瘤学

背景情况:

  • 强度调节辐射疗法 (IMRT) 需要通过试错来手动优化许多治疗计划参数 (TPP).
  • 实现针对患者的剂量分配,以平衡目标覆盖率和处于危险的器官 (OAR) 节省,是复杂和耗时的.
  • 对于具有不确定的权衡和患者变化的场景,需要自动化处方优化.

研究的目的:

  • 开发和验证一个概念验证的人工智能 (AI) 系统,使用自适应神经模糊推理系统 (ANFIS) 来自动化IMRT处方优化.
  • 引导IMRT规划以实现最佳的,与放射瘤学家目标一致的针对患者的处方.
  • 通过模仿专家规划师的调整,提高IMRT规划的准确性和效率.

主要方法:

  • 开发了一个内部ANFIS-AI系统,利用处方剂量 (PD) 约束来指导优化.
  • 该系统调整了TPP,表示为剂量-体积约束,由一个模糊推理系统 (FIS) 提供信息,通过"如果-然后"规则结合专家知识.
  • 为了提高准确性,ANFIS适应性微调了FIS组件 (会员功能,规则强度).

主要成果:

  • ANFIS始终达到剂量测量目标,表现优于传统的FIS.
  • 在C形幻体中,对规划目标体积 (PTV) 的平均剂量合规性有0.7%的改善.
  • 在C形幻体中降低了28%的平均OAR剂量,在前列腺幻体中降低了17.4%和14.1%的平均直肠和膀剂量.

结论:

  • 该ANFIS-AI系统显示了有效和准确的IMRT规划的巨大潜力.
  • 安菲斯有效地优化了患者特定的处方,改善了目标剂量合规性和OAR节省.
  • 这种人工智能方法为集成到临床IMRT工作流程提供了一个有希望的途径.