Computational intelligence methods f...
CIBB (Meeting) (2023 :)

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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 /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Computational intelligence methods for bioinformatics and biostatistics/ edited by Martina Vettoretti ... [et al.].
    其他題名: 18th International Meeting, CIBB 2023, Padova, Italy, September 6-8, 2023 : revised selected papers /
    其他題名: CIBB 2023
    其他作者: Vettoretti, Martina.
    團體作者: CIBB (Meeting)
    出版者: Cham :Springer Nature Switzerland : : 2025.,
    面頁冊數: xix, 332 p. :ill. (chiefly color), digital ;24 cm.
    內容註: 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
    標題: Computational intelligence - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-90714-2
    ISBN: 9783031907142
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