Application of artificial intelligence and machine learning techniques in supporting the diagnosis and treatment of neurological diseases

IF 0.2 Q4 CLINICAL NEUROLOGY
K. Belowska-Bień, B. Bień
{"title":"Application of artificial intelligence and machine learning techniques in\n supporting the diagnosis and treatment of neurological diseases","authors":"K. Belowska-Bień, B. Bień","doi":"10.15557/an.2021.0021","DOIUrl":null,"url":null,"abstract":"The first two decades of the 21st century have seen great advances in artificial\n intelligence and machine learning. The techniques have found their way into everyday\n life, for example in smartphones, search engines, digital customer assistants, motion\n control systems, and biomedical devices. The aims of this paper are to outline the\n possibilities for using artificial intelligence and machine learning techniques in\n supporting the diagnosis and treatment of neurological diseases, and to discuss selected\n applications of these techniques based on the most recent published reports. First,\n contemporary definitions of artificial intelligence and machine learning are presented.\n This is followed by a review of the most important techniques for intelligent data\n processing: search methods, mathematical logic, probabilistic methods, classifiers, and\n artificial neural networks (including deep and convolutional networks). Areas of\n application of these techniques in medicine are identified, including disease diagnosis\n and support of treatment as well as monitoring and prediction of changes in health\n status. The role of artificial intelligence and machine learning in neuroscience is\n presented, together with examples of diagnostic applications based on anatomical,\n morphological and functional brain connectivity data. Sample applications of intelligent\n techniques in supporting the treatment (including surgical management) of nervous system\n diseases are also described. Ambient smart devices monitoring the health status of\n patients with chronic neurological conditions are discussed, and selected projects based\n on smart techniques to support early detection of symptoms of neurodegenerative\n disorders are described. The conclusions highlight the potential of the techniques, as\n well as the challenges and risks associated with them. A possible synergy between\n intelligent systems and actions taken by medical staff is outlined as a way to improve\n the safety and quality of life of patients with acute and chronic neurological\n diseases.","PeriodicalId":41161,"journal":{"name":"Aktualnosci Neurologiczne","volume":" ","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aktualnosci Neurologiczne","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15557/an.2021.0021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 1

Abstract

The first two decades of the 21st century have seen great advances in artificial intelligence and machine learning. The techniques have found their way into everyday life, for example in smartphones, search engines, digital customer assistants, motion control systems, and biomedical devices. The aims of this paper are to outline the possibilities for using artificial intelligence and machine learning techniques in supporting the diagnosis and treatment of neurological diseases, and to discuss selected applications of these techniques based on the most recent published reports. First, contemporary definitions of artificial intelligence and machine learning are presented. This is followed by a review of the most important techniques for intelligent data processing: search methods, mathematical logic, probabilistic methods, classifiers, and artificial neural networks (including deep and convolutional networks). Areas of application of these techniques in medicine are identified, including disease diagnosis and support of treatment as well as monitoring and prediction of changes in health status. The role of artificial intelligence and machine learning in neuroscience is presented, together with examples of diagnostic applications based on anatomical, morphological and functional brain connectivity data. Sample applications of intelligent techniques in supporting the treatment (including surgical management) of nervous system diseases are also described. Ambient smart devices monitoring the health status of patients with chronic neurological conditions are discussed, and selected projects based on smart techniques to support early detection of symptoms of neurodegenerative disorders are described. The conclusions highlight the potential of the techniques, as well as the challenges and risks associated with them. A possible synergy between intelligent systems and actions taken by medical staff is outlined as a way to improve the safety and quality of life of patients with acute and chronic neurological diseases.
人工智能和机器学习技术在支持神经系统疾病诊断和治疗中的应用
21世纪的头二十年见证了人工智能和机器学习的巨大进步。这些技术已经进入了日常生活,例如智能手机、搜索引擎、数字客户助理、运动控制系统和生物医学设备。本文的目的是概述使用人工智能和机器学习技术支持神经系统疾病的诊断和治疗的可能性,并根据最新发表的报告讨论这些技术的选择应用。首先,介绍了人工智能和机器学习的当代定义。接下来是对智能数据处理最重要的技术的回顾:搜索方法、数学逻辑、概率方法、分类器和人工神经网络(包括深度和卷积网络)。确定了这些技术在医学上的应用领域,包括疾病诊断和支持治疗以及监测和预测健康状况的变化。介绍了人工智能和机器学习在神经科学中的作用,以及基于解剖、形态和功能脑连接数据的诊断应用示例。智能技术在支持治疗(包括手术管理)神经系统疾病的样本应用也被描述。讨论了监测慢性神经系统疾病患者健康状况的环境智能设备,并描述了基于智能技术的选择项目,以支持神经退行性疾病症状的早期检测。结论强调了这些技术的潜力,以及与之相关的挑战和风险。智能系统和医务人员采取的行动之间可能的协同作用被概述为改善急慢性神经系统疾病患者的安全和生活质量的一种方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Aktualnosci Neurologiczne
Aktualnosci Neurologiczne CLINICAL NEUROLOGY-
自引率
0.00%
发文量
1
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书