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020 _a9789811608117
024 7 _a10.1007/978-981-16-0811-7
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aR859.7.A78
_b2021 EB
245 0 0 _aArtificial Intelligence and Machine Learning in Healthcare
_cedited by Ankur Saxena, Shivani Chandra
250 _aFirst edition 2021
264 1 _aSingapore
_bSpringer International Publishing
_c2021
300 _a1 recurso en línea (XV, 228 páginas)
_b119 ilustraciones, 88 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aArchivo de texto
_bPDF
490 0 _aBiomedical and Life Sciences (SpringerNature-11642)
490 0 _aBiomedical and Life Sciences (R0) (SpringerNature-43708)
505 0 _aChapter 1_Big Data Analytics and AI for Healthcare -- Chapter 2_Genetics with Big Data and AI -- Chapter 3_AI and Big Data for next-generation sequencing -- Chapter 4_Artificial Intelligence for Computational Biology -- Chapter 5_Artificial intelligence and machine learning in clinical development -- Chapter 6_Big data analytics for personalized medicine -- Chapter 7_Generating and Managing Healthcare data with AI -- Chapter 8_Big Data and Artificial Intelligence for diseases -- Chapter 9_Artificial Intelligence and Big Data for Public Health -- Chapter 10_Biasness in Healthcare Big Data and Computational Algorithms -- Chapter 11_AI and ML in Healthcare: An Ethical perspective.
520 3 _aThis book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.
988 _aSpringer_BiomedLife_2021
650 7 _2embne
_aInteligencia artificial
_9413115
650 7 _2embne
_aBioinformática
_9160489
700 1 _aSaxena, Ankur.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aChandra, Shivani.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
776 0 8 _iPrinted edition:
_z9789811608100
776 0 8 _iPrinted edition:
_z9789811608124
776 0 8 _iPrinted edition:
_z9789811608131
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-0811-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b01/2022
_dz
_eb
_zSI