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Bioinformatics and Biomedical Engineering: 11th International Conference, IWBBIO 2024, Meloneras, Gran Canaria, Spain, July 1517, 2024, Proceedings, Part I 2024 ed. [Minkštas viršelis]

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  • Formatas: Paperback / softback, 359 pages, aukštis x plotis: 235x155 mm, 109 Illustrations, color; 13 Illustrations, black and white; XXVI, 359 p. 122 illus., 109 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Computer Science 14848
  • Išleidimo metai: 23-Aug-2024
  • Leidėjas: Springer International Publishing AG
  • ISBN-10: 3031646282
  • ISBN-13: 9783031646287
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 359 pages, aukštis x plotis: 235x155 mm, 109 Illustrations, color; 13 Illustrations, black and white; XXVI, 359 p. 122 illus., 109 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Computer Science 14848
  • Išleidimo metai: 23-Aug-2024
  • Leidėjas: Springer International Publishing AG
  • ISBN-10: 3031646282
  • ISBN-13: 9783031646287
Kitos knygos pagal šią temą:
This volume constitutes the proceedings of the 11th International Work-Conference on IWBBIO 2023, held in Gran Canaria, Spain, during July 15-17, 2022.





The 54 full papers were carefully reviewed and selected from 148 submissions. They were organized in the following topical sections: Biomarker Identification, Biomedical Engineering, Biomedical Signal Analysis, E-Health.





 
Biomarker Identification.- Elucidating cancer subtypes by using
epigenome and genome cross talk.- Refining Gene Selection and Outlier
Detection in Glioblastoma Based on a Consensus Approach for Regularized
Survival Models.- GPACDA circRNAisease association prediction with generating
polynomials.- Bioinformatics analysis provides insight into the
identification of miRNAs as transcriptional regulators in respiratory
syncytial virus infection.- Biomedical Engineering.- Risk Factors of
Recurrence and Metastasis of Breast Cancer Sub types Based on Magnetic
Resonance Imaging techniques.- Analysis of a Parallel and Distributed BPSO
Algorithm for EEG Classification Impact on Energy Time and Accuracy.- Nave
Bayes for Health Status Predictive Monitoring in COVID 19 Leveraging Drugs
and Diagnoses.- Speech Analysis for Autism Spectrum Disorder Detection for
Children.- SiMHOMer Siamese Models for Health Ontologies Merging and
validation through Large Language Models.- Lossless compression of nanopore
sequencing raw signals.- Medical Equipment Real Time Locating System in
Hospitals based on Bluetooth Low Energy.- Validation of WHO charts mobile
applications for body length and weight assessment in healthy newborns.-
Predicting Atherosclerotic Plaque Onset and Growth in Carotid Arteries A CFD
Driven Approach.- Hemispherical directional reflectance as a screening tool
to distinguish effervescent tablets stored under stress conditions from those
stored in ambient conditions.- Enhanced ergonomics in laryngoscopic surgery
Exploring innovative solutions.- Maximal deadlift strength and bone mass in a
group of healthy elderly men.- Multilayer Networks a survey on models
analysis of algorithms and database.- Bone mineral density in middle aged
former sprinters and middle aged active men.- Biomedical Signal Analysis.-
Spectrum Filtering to Extract Pulse Rate Variability from Signals Recorded by
Wearable Devices.- Machine Learning Model for Anxiety Disorder Diagnosis
based on Sensory Time Series Data.- Analysis of the Relationship between
Electrodermal Activity and Blood Glucose Level in Diabetics.- EEG Based
Detection of REM Sleep Behaviour Disorder Towards a Stage Agnostic Approach.-
Neural network dynamic centers of EEG alpha rhythm for objective assessment
of the state of consciousness in psychopathological conditions.-
Electrocardiogram and Phonocardiogram signal data fusion using Deep Learning
system.- eHealth.- Application of Artificial Intelligence in Healthcare Data
Analytics.- Advancements in Artificial Intelligence for Health A Rapid Review
of AI based Mental Health Technologies Used in the Age of Large Language
Models.- Time series models for predicting the number of patients attending
the emergency department in a local hospital.