UNASSIGNED:粒子群优化(PSO)是一种算法,涉及非线性和多维问题的优化,以最小的参数化达到最佳解决方案。这种元启发式模型已在病理学领域中经常使用。该优化模型在预测阿尔茨海默病时已以多种形式使用。它是一种强大的算法,可以在预测阿尔茨海默病的同时对线性和多模态数据进行处理。PSO技术已经在检测各种疾病中使用了相当长的时间,本文系统地回顾了有关各种PSO技术的论文。
未经评估:要进行系统审查,遵循PRISMA指南,并进行了布尔搜索(“粒子群优化”或“PSO”)和神经影像学和(阿尔茨海默病预测或分类或诊断)。该查询在4个知名数据库中运行:GoogleScholar,Scopus,科学直接,和Wiley出版物。
未经评估:最后分析,纳入10篇论文进行定性和定量综合。PSO在处理单模态和多模态数据时显示出主导特征,同时预测从MCI到阿尔茨海默氏症的转化。从表中可以看出,几乎所有10篇评论论文都具有MRI驱动的数据。在增加其他方式或神经认知措施的同时,提高了准确率。
UNASSIGNED:通过此算法,我们为其他研究人员提供了一个机会,将这种算法与其他最先进的算法进行比较,在看到分类准确性的同时,目的是早期预测MCI进展为阿尔茨海默病。
UNASSIGNED: Particle swarm optimization (PSO) is an algorithm that involves the optimization of Non-linear and Multidimensional problems to reach the best solutions with minimal parameterization. This metaheuristic model has frequently been used in the Pathological domain. This optimization model has been used in diverse forms while predicting Alzheimer\'s disease. It is a robust algorithm that works on linear and multi-modal data while predicting Alzheimer\'s disease. PSO techniques have been in action for quite some time for detecting various diseases and this paper systematically reviews the papers on various kinds of PSO techniques.
UNASSIGNED: To perform the systematic
review, PRISMA guidelines were followed and a Boolean search (\"particle swarm optimization\" OR \"PSO\") AND Neuroimaging AND (Alzheimer\'s disease prediction OR classification OR diagnosis) were performed. The query was run in 4-reputed databases: Google Scholar, Scopus, Science Direct, and Wiley publications.
UNASSIGNED: For the final analysis, 10 papers were incorporated for qualitative and quantitative synthesis. PSO has shown a dominant character while handling the uni-modal as well as the multi-modal data while predicting the conversion from MCI to Alzheimer\'s. It can be seen from the table that almost all the 10 reviewed papers had MRI-driven data. The accuracy rate was accentuated while adding other modalities or Neurocognitive measures.
UNASSIGNED: Through this algorithm, we are providing an opportunity to other researchers to compare this algorithm with other state-of-the-art algorithms, while seeing the classification accuracy, with the aim of early prediction and progression of MCI into Alzheimer\'s disease.