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Updated: Jul 3, 2026

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预测超声向脂质体中的素释放:随机森林和支持矢量机器的比较分析

Ibrahim Shomope1, Kelly M Percival1, Nabil M Abdel Jabbar1

  • 1Department of Chemical and Biological Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates.

Technology in cancer research & treatment
|November 14, 2024
PubMed
概括

随机森林 (RF) 模型在预测低频超声波 (LFUS) 触发的向脂质体的药物释放方面优于支持矢量机器 (SVM). 射频模型在各种功率密度中表现出卓越的精度.

关键词:
人工智能的人工智能是人工智能.石灰中的石灰药物输送是药物输送的过程.药物释放释放药物释放药物释放的时间机器学习是机器学习.功率密度 功率密度 功率密度随机的森林随机的森林支持矢量机器的支持矢量机器.超声波超声波是指超声波的使用.

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Mass Analyzers: Overview01:13

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The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...