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020			_a9783031366789
024	7		_a10.1007/978-3-031-36678-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aR859.7 .A78 _b2023 EB
245	0	0	_aClinical Applications of Artificial Intelligence in Real-World Data _cedited by Folkert W. Asselbergs, Spiros Denaxas, Daniel L. Oberski, Jason H. Moore
250			_a1st ed. 2023
264		1	_aCham _bSpringer International Publishing _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aPart 1: Data Processing, Storage, Regulations -- Biomedical Big Data: Opportunities and Challenges -- Quality Control, Data Cleaning, Imputation -- Data Security And Privacy Issues -- Data Standards and Terminology -- Biomedical Ontologies -- Graph Databases as Future Of Data Storage -- Data Integration, Harmonization -- Natural Language Processing And Text Mining- Turning Unstructured Data Into Structured -- Part 2: Analytics -- Statistical Analysis Statistical Analysis - Causality, Mendelian Randomization -- Statistical Analysis - Meta-Analysis/Reproducibility -- Machine Learning - Basic Concepts -- Machine Learning - Basic Supervised Methods -- Machine Learning - Basic Unsupervised Methods -- Machine Learning - Evaluation -- Machine Learning - Representation Learning/Feature Selection/Engineering -- Machine Learning - Interpretation -- Deep Learning - Prediction -- Deep Learning - Autoencoders -- Artificial Intelligence -- Machine Learning In Practice - Clinical Decision Support, Risk Prediction, Diagnosis -- Machine Learning In Practice - Evaluation Clinical Value, Guidelines -- Challenges Of Machine Learning and AI.
520			_aThis book is a thorough and comprehensive guide to the use of modern data science within health care. Critical to this is the use of big data and its analytical potential to obtain clinical insight into issues that would otherwise have been missed and is central to the application of artificial intelligence. It therefore has numerous uses from diagnosis to treatment. Clinical Applications of Artificial Intelligence in Real-World Data is a critical resource for anyone interested in the use and application of data science within medicine, whether that be researchers in medical data science or clinicians looking for insight into the use of these techniques.
988			_aSpringer_Medicine_2023
650		7	_2embne _9421371 _aInteligencia artificial en medicina
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-36678-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b06/2024 _dz _ean _zSI