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Computational intelligence methods for bioinformatics and biostatistics = 18th International Meeting, CIBB 2023, Padova, Italy, September 6-8, 2023 : revised selected papers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational intelligence methods for bioinformatics and biostatistics/ edited by Martina Vettoretti ... [et al.].
Reminder of title:	18th International Meeting, CIBB 2023, Padova, Italy, September 6-8, 2023 : revised selected papers /
remainder title:	CIBB 2023
other author:	Vettoretti, Martina.
corporate name:	CIBB (Meeting)
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xix, 332 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Computational intelligence - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-90714-2
ISBN:	9783031907142

Computational intelligence methods for bioinformatics and biostatistics = 18th International Meeting, CIBB 2023, Padova, Italy, September 6-8, 2023 : revised selected papers /
Computational intelligence methods for bioinformatics and biostatistics18th International Meeting, CIBB 2023, Padova, Italy, September 6-8, 2023 : revised selected papers /[electronic resource] :CIBB 2023edited by Martina Vettoretti ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xix, 332 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,145131611-3349 ;. - Lecture notes in computer science ;14513..

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.

The book constitutes the refereed post-conference proceedings of the 18th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2023, held in Padova, Italy, during September 6-8, 2023. The 23 full papers presented in these proceedings were carefully reviewed and selected from 24 submissions. They focuses on topics such as machine learning in healthcare informatics and medical biology; machine learning explainability in medical imaging; prediction uncertainty in machine learning; advanced statistical and computational methodologies for single-cell omics data; present and future research in bioinformatics; distributed computing in bioinformatics and computational biology; and modelling and simulation methods for computational biology and systems medicine. .

ISBN: 9783031907142

Standard No.: 10.1007/978-3-031-90714-2doiSubjects--Topical Terms:

704428
Computational intelligence
--Congresses.

LC Class. No.: QH324.2

Dewey Class. No.: 570.285

Computational intelligence methods for bioinformatics and biostatistics = 18th International Meeting, CIBB 2023, Padova, Italy, September 6-8, 2023 : revised selected papers /
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