04237nam a22005295i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050000900172072001600181072002300197072001500220245017900235250001800414264007200432300006500504336002600569337002600595338003600621347002400657490006200681505143500743520076802178650003902946650003602985650003203021650002703053650003903080650003603119650002403155650003203179700008203211700008503293710003403378773002603412776003603438776003603474776003603510830006903546856004603615912001403661912001503675999001703690978-981-99-9029-0DE-He21320251030111425.0cr nn 008mamaa240213s2024    si |    s    |||| 0|eng d  a97898199902909978-981-99-9029-07 a10.1007/978-981-99-9029-02doi 4aQ342 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema10aArtificial Intelligence and Autoimmune Diseasesh[electronic resource] :bApplications in the Diagnosis, Prognosis, and Therapeutics /cedited by Khalid Raza, Surender Singh.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXIX, 323 p. 67 illus., 62 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aStudies in Computational Intelligence,x1860-9503 ;v11330 aAutoimmune 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.  aThe 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. 0aComputational intelligence.964052 0aArtificial intelligence.958441 0aMedical informatics.960693 0aQuantitative research.14aComputational Intelligence.96405224aArtificial Intelligence.95844124aHealth Informatics.24aData Analysis and Big Data.1 aRaza, Khalid.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9709791 aSingh, Surender.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9709802 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981999028308iPrinted edition:z978981999030608iPrinted edition:z9789819990313 0aStudies in Computational Intelligence,x1860-9503 ;v113396885440uhttps://doi.org/10.1007/978-981-99-9029-0  aZDB-2-INR  aZDB-2-SXIT  c57616d57616