• Produktbild: Computational Advances in Bio and Medical Sciences
  • Produktbild: Computational Advances in Bio and Medical Sciences
Band 14548

Computational Advances in Bio and Medical Sciences 12th International Conference, ICCABS 2023, Norman, OK, USA, December 11–13, 2023, Revised Selected Papers

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

22.02.2025

Abbildungen

XIII, 101 illus., 82 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Mukul S. Bansal + weitere

Verlag

Springer

Seitenzahl

278

Maße (L/B/H)

23,5/15,5/1,7 cm

Gewicht

452 g

Sprache

Englisch

ISBN

978-3-031-82767-9

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

22.02.2025

Abbildungen

XIII, 101 illus., 82 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

278

Maße (L/B/H)

23,5/15,5/1,7 cm

Gewicht

452 g

Sprache

Englisch

ISBN

978-3-031-82767-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Computational Advances in Bio and Medical Sciences
  • Produktbild: Computational Advances in Bio and Medical Sciences
  • 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 Alzheimer’s 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 Mover’s Distance.- Functional Connectivity Disruptions in Alzheimer’s 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 Alzheimer’s Disease.