AI and Neuro-Degenerative Diseases: Insights and Solutions

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.

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 experience in 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 developed the 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.