04332nam 22005415 450 991048300000332120200706153823.03-030-40850-710.1007/978-3-030-40850-3(CKB)5300000000003645(MiAaPQ)EBC6132456(DE-He213)978-3-030-40850-3(PPN)243227892(EXLCZ)99530000000000364520200309d2020 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning with Health Care Perspective Machine Learning and Healthcare /edited by Vishal Jain, Jyotir Moy Chatterjee1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (418 pages)Learning and Analytics in Intelligent Systems,2662-3447 ;133-030-40849-3 Includes bibliographical references.Chapter 1: Machine learning for Healthcare: Introduction -- Chapter 2: Artificial Intelligence in Medical Diagnosis: Methods, algorithms and applications -- Chapter 3: Intelligent Learning Analytics in Healthcare Sector Using Machine Learning -- Chapter 4: Unsupervised Learning on Healthcare Survey Data with Particle Swarm Optimization -- Chapter 5: Machine Learning for Healthcare Diagnostics -- Chapter 6: Disease Detection System (DDS) Using Machine Learning Technique -- Chapter 7: Knowledge Discovery (Feature Identification) from Teeth, Wrist and Femur Images to determine Human Age and Gender -- Chapter 8: Deep Learning Solutions for Skin Cancer Detection and Diagnosis -- Chapter 9: Security of Healthcare Systems with Smart Health Records using Cloud Technology -- Chapter 10: Intelligent Heart Disease Prediction on Physical and Mental Parameters: A ML Based IoT and Big Data Application and Analysis -- Chapter 11: Medical Text and image processing: Applications, issues and challenges -- Chapter 12: Machine Learning Methods for Managing Parkinson’s Disease -- Chapter 13: An Efficient Method for Computer-aided Diagnosis of Cardiac Arrhythmias -- Chapter 14: Clinical decision support systems and predictive analytics -- Chapter 15: Yajna and Mantra Science Bringing Health and Comfort to Indo-Asian Public: A Healthcare 4.0 Approach and Computational Study -- Chapter 16: Identifying Diseases and Diagnosis using Machine Learning.This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.Learning and Analytics in Intelligent Systems,2662-3447 ;13Computational intelligenceBiomedical engineeringComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014Biomedical Engineering and Bioengineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/T2700XComputational intelligence.Biomedical engineering.Computational Intelligence.Biomedical Engineering and Bioengineering.610.28563Jain Vishaledthttp://id.loc.gov/vocabulary/relators/edtChatterjee Jyotir Moyedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910483000003321Machine Learning with Health Care Perspective2185799UNINA