论著摘要 |【AI-综述】人工智能技术(自动分析)在神经变性疾病分子成像模式中的角色(双语版)

2018-01-09 13:46:53 admin 1
标签:   人工智能 AI 人工神经网络 神经变性疾病 分子影像 阿尔茨海默病 PET SPECT

Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

发表日期: 2017.02.01   来源:Curr Alzheimer Res. 2017;14(2):198-207.

作者:

Cascianelli S1, Scialpi M1, Amici S1 , Forini N1, Minestrini M1, Fravolini ML1, Sinzinger H1, Schillaci O1, Palumbo B1.

作者介绍:

1. Section of Nuclear Medicine and Health Physics Department of Surgical and Biomedical Sciences, University of Perugia, Perugia, Italy.

摘要

人工智能(AI)是一个非常活跃的计算机科学研究领域,它旨在开发模仿人类智力的系统,并且在许多人类活动(包括医学)中有所帮助。在这篇综述中,我们提出了一些开发AI技术的例子,特别是如人工神经网络(ANN)的自动分类器,它支持向量机(SVM),分类树(ClT)以及诸如随机森林(RF)等集成方法,然后通过正电子发射断层扫描(PET)或单光子发射断层扫描(SPECT)扫描获得的神经变性疾病特别是阿尔茨海默病患者的数据,最后使用以上方法对这些数据进行分析。我们还将注意力集中在在更具代表性的领域(主成分分析 - PCA或部分最小二乘法 - PLS - 这些方法的例子)通过特征选择或投影来进行数据预处理和降维处理的技术;这是处理医疗数据的关键步骤,因为有必要压缩患者信息,并保留最有用的方式,以将受试者分为正常和病理类别。很多文献报道了应用这些技术,通过分子成像模式提取数据来对神经退行性疾病患者进行分类,这也表明计算机辅助诊断系统的不断发展非常有希望对诊断过程作出贡献。

Abstact

Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

阅读原文:PMID: 27334942  DOI: 10.2174/1567205013666160620122926


慧影医疗科技(北京)有限公司

地点:北京市海淀区中关村东升科技园B2-C103

电话:400-890-9020

邮箱:radcloud@huiyihuiying.com

关闭
图片
图片