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020			_a9783030930806
024	7		_a10.1007/978-3-030-93080-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aR859.7.A78 _b2022 EB
245	0	0	_aAI for Disease Surveillance and Pandemic Intelligence : _bIntelligent Disease Detection in Action _cedited by Arash Shaban-Nejad, Martin Michalowski, Simone Bianco
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIX, 331 páginas) _b87 ilustraciones, 63 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-9503 _v1013
505	0		_aDigital Technologies for Clinical, Public and Global Health Surveillance -- Imputing Fine-grain Patterns of Mental Health with Statistical Modelling of Online Data -- Lexical and Acoustic Correlates of Clinical Speech Disturbance in Schizo-phrenia.-A Prognostic Tool to Identify Youth at Risk of at Least Weekly Cannabis Use -- Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Pro-grammed Deep Kernels.-Self-Disclosure in Opioid Use Recovery Forums -- Identifying Prepubertal Children with Risk for Suicide Using Deep Neural Network Trained on Multimodal Brain Imaging -- Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies -- Machine Learning Identification of Self-Reported COVID-19 Symptoms from Tweets in Canada -- RRISK: Analyzing COVID-19 Risk in Food Establishments -- AWS CORD-19 Search: A Neural Search Engine for COVID-19 Literature -- Inferring COVID-19 Biological Pathways from Clinical Phenotypes via Topological Analysis -- The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance -- Interpretable Classification of Human Exercise Videos through Pose Esti-mation and Multivariate Time Series Analysis -- Interpreting Deep Neural Networks for Medical Imaging using Concept Graphs -- Do Deep Neural Networks Forget Facial Action Units? - Exploring the Ef-fects of Transfer Learning in Health Related Facial Expression Recognition -- Utilizing Predictive Analysis to Aid Emergency Medical Services -- Measuring Physiological Markers of Stress During Conversational Agent Interactions -- EvSys: A Relational Dynamic System for Sparse Irregular Clinical Events -- Predicting Patient Outcomes with Graph Representation Learning -- Patient-Specific Seizure Prediction Using Single Seizure Electroenceph-alography Recording -- Evaluation Metrics for Deep Learning Imputation Models -- Logistic Regression Is Also A Black Box. Machine Learning Can Help.
520			_aThis book aims to highlight the latest achievements in the use of artificial intelligence for digital disease surveillance, pandemic intelligence, as well as public and clinical health surveillance. The edited book contains selected papers presented at the 2021 Health Intelligence workshop, co-located with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. While disease surveillance has always been a crucial process, the recent global health crisis caused by COVID-19 has once again highlighted our dependence on intelligent surveillance infrastructures that provide support for making sound and timely decisions. This book provides information for researchers, students, industry professionals, and public health agencies interested in the applications of AI in population health and personalized medicine.
988			_aSpringer_Robotics_2022
650		7	_2embne _9421371 _aInteligencia artificial en medicina
700	1		_aShaban-Nejad, Arash _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMichalowski, Martin _eeditor literario _0(orcid)0000-0003-2060-5878 _1https://orcid.org/0000-0003-2060-5878 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aBianco, Simone _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030930790
776	0	8	_iPrinted edition: _z9783030930813
776	0	8	_iPrinted edition: _z9783030930820
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-93080-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b06/2022 _dz _eIG _zSI