04335nam a22005055i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001300172072001600185072002300201072001500224245023400239250001800473264006900491300006700560336002600627337002600653338003600679347002400715490004100739505150200780520068902282650002802971650002302999650003203022650004403054650004203098650002403140700015003164700015603314700008803470710003403558773002603592776003603618776003603654830004803690856004603738912001403784912001403798999001703812978-3-031-59216-4DE-He21320251030112019.0cr nn 008mamaa240429s2024    sz |    s    |||| 0|eng d  a97830315921649978-3-031-59216-47 a10.1007/978-3-031-59216-42doi 4aR856-857 7aMQW2bicssc 7aTEC0590002bisacsh 7aMQW2thema10aInternational Conference on Biomedical and Health Informatics 2022h[electronic resource] :bProceedings of ICBHI 2022, November 24–26, 2022, Concepción, Chile /cedited by Esteban Pino, Ratko Magjarević, Paulo de Carvalho.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXIV, 314 p. 135 illus., 114 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aIFMBE Proceedings,x1433-9277 ;v1080 aData-driven Model for Long-term Prediction of Blood Glucose in Type 2 Diabetes -- Semantic of Automatically Generated Interval-valued Memberships Functions in Brain Magnetic Resonance Images -- Egfr Mutation Prediction Using F18-fdg Pet-ct Based Radiomics Features in Non-small Cell Lung Cancer -- Breast Cancer Risk Analysis Using Deep Learning on Multi-omics Data Combined with Epigenetic Factors -- Predicting Depression History from a Short Reward/Aversion Task with Behavioral Economic Features -- Machine Learning Algorithm for Epileptic Seizure Prediction from Scalp Eeg Records -- Evaluating the Social Media Users’ Mental Health Status During Covid-19 Pandemic Using Deep Learning -- A System Detection of Atrial Fibrillation Using One Ecg Derivation and Inductive Transfer Learning -- Interpretability and Explainability of Machine Learning Models: Achievements and Challenges -- Cardiovascular Risk Assessment: An Interpretable Machine Learning Approach -- Explainability: Actionable Information Extraction -- Analysis, Design and Development of a Digital Application Prototype for Cognitive Assessment and Training -- Voces – an Open Database of Child and Youth Vowels in Spanish for Research Purposes -- Rehastart: Cognitive Tele-rehabilitation Empowered by Vision Transformers -- Development of a Dashboard Analytics Platform for Dementia Caregivers to Understand Diagnostic Test Results -- Usability of the Peruvian National Death Informatics System Sinadef by Attention Levels.  aThis book covers current advances and challenges in biomedical and health informatics. It reports on the latest technologies and on strategies and concepts to implement them for medicine, health and education. Contributions deals with a range of topics, including artificial intelligence and precision medicine, e-health and training, medical devices and wearables, and medical imaging. Gathering the proceedings of the Fifth International Conference on Biomedical and Health Informatics (ICBHI 2022), held on November 24–26, 2022, in Concepción, Chile, this books provides academics and professionals with a timely snapshot of the digital transformation in the field of medicine. 0aBiomedical engineering. 0aSignal processing. 0aMedical informatics.96069314aBiomedical Devices and Instrumentation.24aDigital and Analog Signal Processing.24aHealth Informatics.1 aPino, Esteban.eeditor.0(orcid)0000-0002-2636-051X1https://orcid.org/0000-0002-2636-051X4edt4http://id.loc.gov/vocabulary/relators/edt9760361 aMagjarević, Ratko.eeditor.0(orcid)0000-0002-7260-39061https://orcid.org/0000-0002-7260-39064edt4http://id.loc.gov/vocabulary/relators/edt9657101 ade Carvalho, Paulo.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9760372 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303159215708iPrinted edition:z9783031592171 0aIFMBE Proceedings,x1433-9277 ;v10896571340uhttps://doi.org/10.1007/978-3-031-59216-4  aZDB-2-ENG  aZDB-2-SXE  c59506d59506