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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Order before 4pm tomorrow for delivery by Wed 21 Jan 2026.

A Paperback by Martina Vettoretti

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    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
    Also in:
    Computer science

    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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