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Computational Advances in Bio and Medical Sciences: 12th International Conference, ICCABS 2023, Norman, OK, USA, December 1113, 2023, Revised Selected Papers [Minkštas viršelis]

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  • Formatas: Paperback / softback, 278 pages, aukštis x plotis: 235x155 mm, 82 Illustrations, color; 19 Illustrations, black and white; XIII, 278 p. 101 illus., 82 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Bioinformatics 14548
  • Išleidimo metai: 22-Feb-2025
  • Leidėjas: Springer International Publishing AG
  • ISBN-10: 3031827678
  • ISBN-13: 9783031827679
Kitos knygos pagal šią temą:
Computational Advances in Bio and Medical Sciences: 12th International Conference, ICCABS 2023, Norman, OK, USA, December 1113, 2023, Revised Selected PapersDidesnis paveikslėlis
  • Formatas: Paperback / softback, 278 pages, aukštis x plotis: 235x155 mm, 82 Illustrations, color; 19 Illustrations, black and white; XIII, 278 p. 101 illus., 82 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Bioinformatics 14548
  • Išleidimo metai: 22-Feb-2025
  • Leidėjas: Springer International Publishing AG
  • ISBN-10: 3031827678
  • ISBN-13: 9783031827679
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9783031827679.html
Raktažodžiai:
This book constitutes the refereed proceedings of the 12th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2023, held in Norman, Oklahoma, USA, during December 1113, 2023.





The 23 full papers included in this book were carefully reviewed and selected from 65 submissions. These papers focus on the recent advances in Computational techniques and applications in the areas of Biology, Medicine, and Drug discovery.
An Explainable Deep Learning Framework for Mandibular Canal Segmentation
from Cone Beam Computed Tomography Volume.- Identification of Chimeric RNAs:
A Novel Machine Learning Perspective.- PartialFibers: An Efficient Method for
Predicting Drug-Drug Interactions.- Optimizing Deep Learning for Biomedical
Imaging.- Exploring a Solution Curve in the Phase Plane for Extreme Firing
Rates in the Izhikevich Model.- Cancer and Tissue Prediction Using Mutational
Signatures in Highly Mutated Cancers.- On the Hardness of Wildcard Pattern
Matching on de Bruijn Graphs.- Plastic: An Easy to use and Modular Tool for
Designing Tumor Phylogeny Reconstruction Pipelines.- A 3D Deep Learning
Architecture for Denoising Low-Dose CT Scans.- A Simple and Interpretable
Deep Learning Model for Diagnosing Pneumonia from Chest X-Ray Images.- FedDP:
Secure Federated Learning with Differential Privacy for Disease Prediction.-
Computational Tumor Progression Analysis via Seriation based Trajectory
Inference.- Multilayer Network Analysis of Brain Signals for Detecting
Alzheimers Disease.- DNA Methylation Based Subtype Classification of Breast
Cancer.- Repeated Measures Latent Dirichlet Allocation for Longitudinal
Microbiome Analysis.- Improving Disease Comorbidity Prediction with
Biologically Supervised Graph Embedding.- Lightweight and Generalizable Model
for COVID-19 Detection Using Chest Xray Images.- Decoding Heterogeneity in
Quadruple-Negative Breast Cancer: A Data-Driven Clustering Approach.-
Determining Temporal Linkages in Dynamic Epidemiological Networks Using the
Earth Movers Distance.- Functional Connectivity Disruptions in Alzheimers
Disease: A Maximum Flow Perspective.- On Multi-Phase Metagenomics Reads
Binning.- A Unified Machine Learning Framework for Multi-subtype Tumour
Classification across Diverse Datasets.- AFA: Abstract Functional Analysis
Identifies New Microglial Subtypes at Single Cell Level in Alzheimers
Disease.