Description

Book Synopsis

.- A Network Approach to Aquatic Food Web Dynamics.

.- Leveraging Diffuser Data Augmentation to enhance ViT-based performance on Dermatoscopic Melanoma Images Classification.

.- Thyroid Nodule Diagnosis Using a New Supervised Autoencoder Neural net work with multi-categorical medical data.

.- Can smoothing methods recognize the patterns of the hazard function in complex clinical scenarios? A simulation study using discrete-time survival models.

.- Nested Named Entity Recognition in Chinese Electronic Medical Records.

.- Transformers for Interpretable Classification of Histopathological Images.

.- Breast Cancer Malignancy Prediction Through Explainable Models based on a Multimodal Signature of Features.

.- Exploring the Conformational Odorant Space in the Olfactory Re-ceptor Binding Region.

.- Synergy between mechanistic modelling and Ensemble Feature Selection ap proaches to explore multiscale biological Heterogeneity.

.- Homophily of large weighted networks in a data streaming setting.

.- Living along COVID-19: assessing contention policies through Agent-Based Models.

.- Stochastic modeling and dosage optimization of a cancer vaccine exploiting the EpiMod Framework.

.- Extension of the GreatMod modeling framework to simulate non-Markovian processes with general-distributed events.

.- Identifying Damage-Related Features in scRNA-seq Data.

.- A benchmark study of gene fusion prioritization tools.

.- Improving the reliability of tree-based feature importance via consensus signals.

.- Interpretable Machine Learning for Automated Cellular Population Analysis in Flow Cytometry.

.- Pre-trained Models Based on Primary Sequence to Classify Antibody Bind ing to Protein and Non-Protein Targets with 80% Accuracy.

.- Inferring breast cancer subtype associations using an original omics integra tion based on Non-negative Matrix Tri-Factorization.

.- Screening the bioactivity of the P450 enzyme by spiking neural networks.

.- Enhancing functional interpretability in gene expression analysis through biologically-guided feature selection.

.- Extraction of Attributes from Electrodermal Activity Signals Applying Time Series Fuzzy Granulation for Classification of Academic Stress Perception in Different Scenarios.

.- Transfer Learning and AutoML as a Support for the Pneumonia Diagnosis using Chest X-ray scan.

Computational Intelligence Methods for

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    £85.49

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    RRP £89.99 – you save £4.50 (5%)

    Order before 4pm tomorrow for delivery by Wed 17 Jun 2026.

    A Paperback by Martina Vettoretti

    15 in stock


      View other formats and editions of Computational Intelligence Methods for by Martina Vettoretti

      Publisher: Springer
      Publication Date: 5/23/2025
      ISBN13: 9783031907135, 978-3031907135
      ISBN10: 3031907132

      Description

      Book Synopsis

      .- A Network Approach to Aquatic Food Web Dynamics.

      .- Leveraging Diffuser Data Augmentation to enhance ViT-based performance on Dermatoscopic Melanoma Images Classification.

      .- Thyroid Nodule Diagnosis Using a New Supervised Autoencoder Neural net work with multi-categorical medical data.

      .- Can smoothing methods recognize the patterns of the hazard function in complex clinical scenarios? A simulation study using discrete-time survival models.

      .- Nested Named Entity Recognition in Chinese Electronic Medical Records.

      .- Transformers for Interpretable Classification of Histopathological Images.

      .- Breast Cancer Malignancy Prediction Through Explainable Models based on a Multimodal Signature of Features.

      .- Exploring the Conformational Odorant Space in the Olfactory Re-ceptor Binding Region.

      .- Synergy between mechanistic modelling and Ensemble Feature Selection ap proaches to explore multiscale biological Heterogeneity.

      .- Homophily of large weighted networks in a data streaming setting.

      .- Living along COVID-19: assessing contention policies through Agent-Based Models.

      .- Stochastic modeling and dosage optimization of a cancer vaccine exploiting the EpiMod Framework.

      .- Extension of the GreatMod modeling framework to simulate non-Markovian processes with general-distributed events.

      .- Identifying Damage-Related Features in scRNA-seq Data.

      .- A benchmark study of gene fusion prioritization tools.

      .- Improving the reliability of tree-based feature importance via consensus signals.

      .- Interpretable Machine Learning for Automated Cellular Population Analysis in Flow Cytometry.

      .- Pre-trained Models Based on Primary Sequence to Classify Antibody Bind ing to Protein and Non-Protein Targets with 80% Accuracy.

      .- Inferring breast cancer subtype associations using an original omics integra tion based on Non-negative Matrix Tri-Factorization.

      .- Screening the bioactivity of the P450 enzyme by spiking neural networks.

      .- Enhancing functional interpretability in gene expression analysis through biologically-guided feature selection.

      .- Extraction of Attributes from Electrodermal Activity Signals Applying Time Series Fuzzy Granulation for Classification of Academic Stress Perception in Different Scenarios.

      .- Transfer Learning and AutoML as a Support for the Pneumonia Diagnosis using Chest X-ray scan.

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