AI and Neuro-Degenerative Diseases: Insights and Solutions
暫譯: 人工智慧與神經退化性疾病：洞察與解決方案
Gaur, Loveleen, Abraham, Ajith, Ajith, Reuel
相關主題
商品描述
This book explores the current state of healthcare practice and provides a roadmap for harnessing artificial intelligence (AI) and other modern cognitive technologies for neurogenerative diseases. The main goal of this book is to look at how these techniques can be used to classify patients with neurodegenerative diseases by extracting data from multiple modalities. It demonstrates that the growing development of computer-aided diagnosis systems has a lot of potential to help with the diagnostic process. It offers an analysis of the prospective and perils in implementing such state of the art.
Progressive brain disorders with a high prevalence in the general population include Parkinson's disease, Alzheimer's disease and other types of dementia, Huntington's disease, and motor neuron disease. Worldwide, it is estimated that 33 million people have Alzheimer's disease, and 10 million people have Parkinson's disease. The global health economy is significantly impacted by these disorders, which affect both the patient and the caregivers. Various diagnostic techniques are used for differential diagnoses, such as brain imaging, EEG analysis, molecular analysis, and cognitive, psychological, and physical examination. The book aims to develop effective treatments, enhance patient quality of life, and extend life expectancy. It focuses on novel artificial intelligence approaches to clarify the pathogenesis of neurodegenerative disorders and provide early diagnosis.The authors compile recent developments based on machine learning and deep learning techniques to diagnose neurodegenerative diseases using imaging, genetic, and clinical data. The authors support initiatives and methods that aim to improve the application of algorithms in diagnostic practice.商品描述(中文翻譯)
這本書探討了當前醫療實踐的狀態，並提供了一個利用人工智慧（AI）及其他現代認知技術來應對神經退行性疾病的路線圖。本書的主要目標是研究如何利用這些技術通過從多種模態中提取數據來對神經退行性疾病患者進行分類。它展示了計算機輔助診斷系統的日益發展在幫助診斷過程中具有很大的潛力。它還分析了實施這些尖端技術的前景與風險。
在一般人群中，高盛行率的進行性腦部疾病包括帕金森病、阿茲海默病及其他類型的癡呆症、亨廷頓病和運動神經元病。根據全球估計，約有3300萬人患有阿茲海默病，1000萬人患有帕金森病。這些疾病對全球健康經濟造成了重大影響，影響到患者及其照護者。各種診斷技術被用於鑑別診斷，例如腦部影像學、腦電圖（EEG）分析、分子分析以及認知、心理和身體檢查。本書旨在開發有效的治療方法，提升患者的生活品質，並延長壽命。它專注於新穎的人工智慧方法，以澄清神經退行性疾病的發病機制並提供早期診斷。
作者根據機器學習和深度學習技術的最新發展，利用影像、基因和臨床數據來診斷神經退行性疾病。作者支持旨在改善算法在診斷實踐中應用的倡議和方法。
作者簡介
Dr. Loveleen Gaur is currently working as an adjunct professor with Taylor University, Malaysia & University of South Pacific, Fiji and academic consultant with Australian School of Graduate Studies. Before moving to USA, she was working as Professor with Amity University, India. She has supervised several PhD scholars, Post Graduate students, mainly in Artificial Intelligence and Data Analytics for business and healthcare. Under her guidance, the AI/Data Analytics research cluster has published extensively in high impact factor journals and has established extensive research collaboration globally with several renowned professionals.
She is a senior IEEE member and Series Editor with CRC and Wiley. She has high indexed publications in SCI/ABDC/WoS/Scopus and has several Patents/copyrights on her account, edited/authored many research books published by world-class publishers. She has excellent experiencein supervising and co-supervising postgraduate and PhD students internationally. An ample number of Ph.D. and master's students graduated under her supervision. She is an external Ph.D./Master thesis examiner/evaluator for several universities globally. She has also served as Keynote speaker for several international conferences, presented several Webinars worldwide, chaired international conference sessions. Prof. Gaur has significantly contributed to enhancing scientific understanding by participating in many scientific conferences, symposia, and seminars, by chairing technical sessions and delivering plenary and invited talks.
She has specialized in the fields of Artificial Intelligence, Machine Learning, Pattern Recognition, Internet of Things, Data Analytics and Business Intelligence. She has chaired various positions in International Conferences of repute and is a reviewer with top rated journals of IEEE, SCI and ABDC Journals. She has been honored with prestigious National and International awards.
She has introduced courses related to Artificial Intelligence specialization including, Predictive Analytics, Deep and Reinforcement learning etc. She has vast experience teaching advanced-era specialized courses, including Predictive Analytics, Data Visualization, Social Network Analytics, Deep Learning, Power BI, Digital Marketing and Digital Innovation etc., besides other undergraduate and postgraduate courses, graduation projects, and thesis supervision.
Dr. Ajith Abraham is the current Dean of the Faculty of Computing and Data Sciences at FLAME University, India. He is also a Professor of Artificial Intelligence. He is the Founding Director of Machine Intelligence Research Labs, a not-for-profit Scientific Network for Innovation and Research Excellence connecting industry and academia. The Network with HQ in Seattle, USA has currently more than 1,500 scientific members from over 105 countries. As an Investigator / Co-Investigator, he has won research grants worth over 100+ Million US$. He has over 33 years of industry and academic experience. His primary research is on developing advanced machine intelligence using hybridization of function approximation methods, approximate reasoning and global optimization methods focused on big data analytics, understanding networks, information security, Web intelligence, decision support systems, the Internet of Things, etc.
He has authored or co-authored more than 1,400 research publications out of which there are 100+ books covering various aspects of Computer Science. One of his books was translated to Japanese and few other articles were translated to Russian and Chinese. Dr. Abraham has more than 50,000+ academic citations (h-index of 105+ as per google scholar). He has given more than 150 plenary lectures and conference tutorials (in 20+ countries). Dr. Abraham was the Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (which has over 200+ members) during 2008-2021 and served as a Distinguished Lecturer of IEEE Computer Society representing Europe (2011-2013). Dr. Abraham was the editor-in-chief of Engineering Applications of Artificial Intelligence (EAAI) during 2016-2021 and serves/served the editorial board of over 15 International Journals indexed by Thomson ISI. He received Ph.D. in Computer Science from Monash University, Melbourne, Australia (2001) and a Master of Science degree in Control and Automation from Nanyang Technological University, Singapore. He holds a Bachelor's Degree in Electrical and Electronic Engineering from the University of Calicut, India.
Dr. Reuel Ajith finished MD degree in June 2021 from the Faculty of Medicine in Vilnius University, Lithuania. His research interests are in Internal medicine with a focus on neuro-degenerative diseases. He was in a team of researchers that developedthe usage of artificial intelligence and free-speech to detect early signs of Parkinson's disease. The early detection mechanism used signal and speech processing techniques integrated with machine learning algorithms. He is affiliated with Machine Intelligence Research Labs (MIR Labs) dealing with AI and health care related projects.
作者簡介(中文翻譯)
**Dr. Loveleen Gaur** 目前擔任馬來西亞泰勒大學及斐濟南太平洋大學的兼任教授，並擔任澳洲研究生學校的學術顧問。在移居美國之前，她曾在印度的阿米提大學擔任教授。她指導過多位博士生和研究生，主要專注於人工智慧和商業及醫療保健的數據分析。在她的指導下，**AI/數據分析研究群**在高影響因子期刊上發表了大量研究，並與多位知名專業人士在全球範圍內建立了廣泛的研究合作。
她是資深的IEEE會員，並擔任CRC和Wiley的系列編輯。她在SCI/ABDC/WoS/Scopus上有**高引用的出版物**，並擁有多項**專利/著作權**，編輯或撰寫了多本由世界級出版社出版的**研究書籍**。她在國際上擁有豐富的**指導和共同指導研究生及博士生**的經驗，許多博士和碩士生在她的指導下畢業。她是多所全球大學的**外部博士/碩士論文考官/評估者**。她還曾擔任多個國際會議的**主題演講者**，在全球範圍內舉辦了多場**網路研討會**，並主持國際會議的會議。Gaur教授通過參加許多科學會議、研討會和座談會，擔任技術會議的主席並發表專題演講，顯著促進了科學理解。
她專注於人工智慧、機器學習、模式識別、物聯網、數據分析和商業智慧等領域。她在多個知名國際會議中擔任各種職位，並是IEEE、SCI和ABDC期刊的評審。她曾獲得多項國內外的榮譽獎項。
她引入了與人工智慧專業相關的課程，包括預測分析、深度學習和強化學習等。她在教授高級專業課程方面擁有豐富的經驗，包括預測分析、數據視覺化、社交網絡分析、深度學習、Power BI、數位行銷和數位創新等，此外還教授其他本科和研究生課程、畢業專案和論文指導。
**Dr. Ajith Abraham** 是印度FLAME大學計算與數據科學學院的院長，同時也是人工智慧的教授。他是機器智能研究實驗室的創始主任，這是一個非營利的科學創新與研究卓越網絡，連接產業與學術。該網絡總部位於美國西雅圖，目前擁有來自105個國家的1,500多名科學成員。作為研究者/共同研究者，他獲得了超過1億美元的研究資助。他擁有超過33年的產業和學術經驗。他的主要研究集中在利用功能近似方法、近似推理和全球優化方法的混合來開發先進的機器智能，專注於大數據分析、網絡理解、信息安全、網絡智能、決策支持系統、物聯網等。
他已經撰寫或共同撰寫了超過1,400篇研究出版物，其中有100多本書涵蓋計算機科學的各個方面。他的一本書被翻譯成日文，其他幾篇文章被翻譯成俄文和中文。Dr. Abraham 擁有超過50,000次的學術引用（根據Google Scholar的h-index為105以上）。他在20多個國家發表了超過150場專題演講和會議教程。Dr. Abraham在2008年至2021年間擔任IEEE系統人與控制論學會軟計算技術委員會的主席（該委員會擁有超過200名成員），並於2011年至2013年擔任IEEE計算機學會的傑出講者，代表歐洲。Dr. Abraham在2016年至2021年間擔任《人工智慧工程應用》（EAAI）的主編，並服務於超過15本由Thomson ISI索引的國際期刊的編輯委員會。他於2001年在澳大利亞墨爾本的莫納什大學獲得計算機科學博士學位，並在新加坡南洋理工大學獲得控制與自動化的碩士學位。他擁有印度卡利卡特大學的電氣與電子工程學士學位。
**Dr. Reuel Ajith** 於2021年6月在立陶宛維爾紐斯大學醫學院獲得醫學博士學位。他的研究興趣集中在內科，特別是神經退行性疾病。他曾參與一個研究團隊，開發利用人工智慧和語音識別技術來檢測帕金森病的早期跡象。該早期檢測機制使用了信號和語音處理技術，並結合了機器學習算法。他與機器智能研究實驗室（MIR Labs）有關聯，專注於人工智慧和醫療保健相關的專案。
