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.
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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.
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1. Demystifying: The Role of Artificial Intelligence in Neurodegenerative Diseases.- 2. Role Of Artificial Intelligence and Internet of Things in Neurodegenerative Diseases.- 3. Explainable Artificial Intelligence (XAI) on Neurogenerative Diseases.- 4. Clinical Genomics to Drug Discovery Using Machine Learning for Neurodegenerative disorders: A Future Perspective.- 5. Amyotrophic Lateral Sclerosis (ALS) Monitoring using Explainable AI.- 6. Prevalence of Dementia in India.- 7. Exploring AI's Role in Managing Neurodegenerative Disorders: Possibilities and Hurdles.- 8. Artificial Intelligence in Neuro Degenerative Diseases: Opportunities and Challenges.- 9. Ethical considerations: Case Scenarios.
Les mer
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.
Les mer
Explores the current state of healthcare practice and provides a roadmap for harnessing artificial intelligence Focuses on novel artificial intelligence approaches to clarify the pathogenesis of neurodegenerative disorders Looks at how these techniques can be used to classify patients with neurodegenerative diseases by extracting data
Les mer

Produktdetaljer

ISBN
9783031531477
Publisert
2024-04-09
Utgiver
Vendor
Springer International Publishing AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Om bidragsyterne

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. Abraham is the Officiating Vice Chancellor at Bennett University, India. Prior to this, he was the Dean of Faculty of Computing andMathematical Sciences at FLAME University and the Director of Machine Intelligence Research Labs (MIR Labs), a Not-for-Profit Scientific Network forInnovation and Research Excellence connecting Industry and Academia. As an Investigator / Co-Investigator, he has won research grants worth over 100+ Million US$. During the last five years, he has held two University Professorial appointments: Professor of Artificial Intelligence in Innopolis University, Russia and the Yayasan TunIsmail Mohamed Ali Professorial Chair in Artificial Intelligence of UCSI, Malaysia. Dr. Abraham works in a multi-disciplinary environment, and he has authored / co-authored more than 1,500+ research publications out of which there are 100+ books covering various aspects of Computer Science. One of his books was translated to Japanese and a few other articles were translated to Russianand Chinese. Dr. Abraham has more than 57,000+ academic citations (h-index of 114+as per google scholar). He has given more than 200+ 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 DistinguishedLecturer of IEEE Computer Society representing Europe (2011-2013). Dr. Abraham was the editor-in-chief of Engineering Applications of Artificial Intelligence,Elsevier during 2016-2021 and serves / served on the editorial board of over 15International Journals indexed by Thomson ISI. Dr. Abraham received Ph.D.degree in Computer Science from Monash University, Melbourne, Australia (2001),Master of Science Degree from Nanyang Technological University, Singapore(1998) and B.Tech (Hons) degree in Electrical and Electronic Engineering fromUniversity of Calicut in 1990.

Dr. Reuel Ajith finished MD degree in June 2021 from the Faculty of Medicine in Vilnius University, Lithuania. His research interests are in Cardiology and 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. Currently is practicing Cardiology in the Ameos Klinikum St Clemens, Oberhausen, Germany.