The book provides an overview of various autoimmune disorders and how artificial intelligence (AI) and machine learning will be used for the diagnosis, prognosis, and treatment of these disorders. AI algorithms are used to create synthetic patient populations with the properties of actual patient cohorts, build personalized predictive models of drug combinations and unravel complex relationships between diet, microbiome, and genetic line-up to determine the comparative treatment response. The book highlights clinical applications and challenges of AI for the diagnosis and treatment/management of autoimmune disorders which includes Rheumatoid Arthritis (RA), Multiple Sclerosis (MS), Type I Diabetes, Psoriatic Arthritis (PsA), and other critical diseases.

Covers fundamental concepts of auto-immune diseases Presents recent developments in AI-based diagnosis of various auto-immune diseases Covers applications of ML and DL in the prognosis and treatment planning and management of auto-immune diseases

Autorentext

Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia (Central University), New Delhi, India. He has also served as the ICCR Chair Visiting Professor at the Faculty of Computer & Information Sciences, Ain Shams University, Cairo, Egypt. Dr. Raza has over 13 years of teaching and research experience. He has contributed over 110 peer-reviewed research articles in refereed international journals, conference proceedings, and book chapters. Dr. Raza has authored/edited 7 Books published by reputed publishers like Springer-Nature, Elsevier, and CRC Press. Dr. Raza is an Academic Editor of PeerJ Computer Science, and Guest Editor of the Journal Natural Product Communications. He has active collaborations with scientists from leading institutions in India and abroad. He has received grants for two Govt. funded research projects and worked as Principal Investigator. Dr. Raza has delivered several keynote addresses, invited talks, public lectures, and seminars at National and International conferences and workshops, and chaired technical sessions at various National and International conferences. Dr. Raza has been featured in the list of the World's Top 2% Scientists released by Stanford University (USA) in collaboration with Elsevier for two consecutive years 2021 and 2022. He is a Life Member of the Computer Society of India (CSI) and Soft Computing Research Society, and a Regular Member of Machine Intelligence Research (MIR) Lab, USA. 

Dr. Surender Singh is Professor at the Department of Pharmacology, All India Institute of Medical Sciences (AIIMS), New Delhi, India. Dr. Singh has teaching and research experience of more than 30 years. He is Fellow of National Academy of Medical Sciences (FAMS), India, Fellow of Royal Society of Chemistry (FRSC), UK, Fellow of International Medical Science Academy (FIMSA), India, Fellow of Institution of Chemists (FIC), India, Fellow of International Council of Ayurveda (FICA), India, Member of New York Academy of Sciences, USA, and D.Sc. (Honoris Causa), Colombo, Sri Lanka. Dr. Singh has published over 150 Research Papers, authored/edited over 10 Books and Scientific Series, guided over 65 theses (MD, MDS, M Pharm, MSc, PhD, PDF), and completed over 35 research projects funded by various finding agencies including ICMR, DBT, AIIMS, AYUSH, Govt. of India. His research interest lies in autoimmune diseases, and AI applications in autoimmune diseases.

Inhalt

Autoimmune Disorders: Types, Symptoms and Risk Factors.- Immune System and Autoimmunity: Cellular and Molecular Mechanisms.- Autoimmune Diseases: Recent Insights on Epidemiology, Pathogenesis and Prevalence Rate.- The Role of Artificial Intelligence and Machine learning in Autoimmune Disorders.- Autoimmune Autonomic Disorder: AI-based Diagnosis and Prognosis.- Detection of Rheumatoid Arthritis using CNN in Autoimmune Diseases Disorders.- The Emerging Applications of Machine Learning in the Diagnosis of Multiple Sclerosis.- Exploring State-of-the-art CNN Models for Early Detection of Multiple Sclerosis using MRI Images.- AI-assisted Model for Risk Detection of Autoimmune Diseases.- Artificial Intelligence in the Diagnosis and Treatment of Rheumatoid Arthritis: Current Status and Future Perspectives.- Data Analytics for Diagnosis, Tracking, and Treatment Planning in Autoimmune Diseases using AI.- Role of Artificial Intelligence in the Treatment Management of Psoriatic Arthritis.- Artificial Intelligence, Machine Learning and Deep Learning in the Diagnosis and Treatment of Rheumatoid Arthritis: Case Studies.- Artificial Intelligence and Machine Learning Techniques in the Diagnosis of Type I Diabetes: Case Studies.- Computational Intelligence Methods for Biomarkers Discovery in Autoimmune Diseases: Case Studies.- AI-empowered Prediction of Prognosis and Treatment Response in Rheumatoid arthritis