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多目标优化框架,通过遗传算法规划前列腺瘤激光切除手术.

Gabriele Adabbo¹, Assunta Andreozzi², Marcello Iasiello²

¹Università degli Studi del Molise, Dipartimento di Medicina e Scienze della Salute "Vincenzo Tiberio", Via Francesco de Sanctis 1 86100 Campobasso, Italy.

Computer methods and programs in biomedicine

|May 9, 2025

概括

这项研究优化了激光诱导的前列腺癌热除,通过将遗传算法和有限元素模拟相结合. 该方法确定了最大限度的瘤破坏的最佳设置,同时最大限度地减少对健康组织的损伤.

关键词:

贝叶斯人造神经网络是贝叶斯人的人工神经网络.转移生物热的转移生物热.遗传算法遗传算法遗传算法激光切除术是一种激光切除术.多目标优化多目标优化前列腺癌是什么意思前列腺癌是什么意思

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科学领域:

在瘤学瘤学.
生物医学工程生物医学工程
计算科学计算科学

背景情况:

前列腺癌很常见,许多患者接受过度治疗.
像激光诱导高热症这样的最小侵入性疗法可以替代手术,放射和化疗.
激光诱导的热性切除缺乏标准化,可能会损害健康的前列腺组织.

研究的目的:

为了在前列腺瘤中进行激光诱导的热除,进行多目标优化.
为了确定最佳的程序设置,平衡癌症治疗和健康组织的保存.
开发一种标准化的协议,用于激光热切除前列腺癌.

主要方法:

将有限元模拟与用于多目标优化的遗传算法结合起来.
使用Pennes的生物热方程式来模拟瘤和健康的前列腺组织的热损伤.
开发线性回归和贝叶斯人造神经网络,以将治疗变量与结果相关联.

主要成果:

多目标遗传算法有效地确定了最佳的治疗设置.
一种权衡解决方案实现了完全的瘤缩,对健康的前列腺造成的损伤最小 (188毫米3).
人工神经网络提供了比线性回归更好的预测准确度.

结论:

开发了一种有效的方法来优化激光诱导的热除协议.
结合遗传算法和有限元模拟,可以选择最佳时间和激光设置.
这种方法有助于外科医生规划前列腺癌治疗,减少结果的不确定性.