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Enhancing the Human Health Status Prediction: The ATHLOS Project

Applied artificial intelligence, 2021-09, Vol.35 (11), p.834-856

2021

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P72Inferring systems-level cardiac aging biomarkers through integromics network analysis

Cardiovascular research, 2014-07, Vol.103 (suppl 1), p.S12-S12

2014

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A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project

Health information science and systems, 2022-04, Vol.10 (1), p.6-6, Article 6

2022

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Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning

Sensors (Basel, Switzerland), 2023-04, Vol.23 (9), p.4184

2023

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COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods

International journal of environmental research and public health, 2023-01, Vol.20 (3), p.2035

2023

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An Ensemble Feature Selection Approach for Analysis and Modeling of Transcriptome Data in Alzheimer’s Disease

Applied sciences, 2023-02, Vol.13 (4), p.2353

2023

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Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

IEEE transactions on evolutionary computation, 2011-02, Vol.15 (1), p.99-119

2011

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A Comparison of the Various Methods for Selecting Features for Single-Cell RNA Sequencing Data in Alzheimer’s Disease

Advances in experimental medicine and biology, 2023, Vol.1424, p.241-246

2023

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A Network-Based Perspective in Alzheimer's Disease: Current State and an Integrative Framework

IEEE journal of biomedical and health informatics, 2019-01, Vol.23 (1), p.14-25

2019

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Assessing and Modelling of Post-Traumatic Stress Disorder Using Molecular and Functional Biomarkers

Biology (Basel, Switzerland), 2023-07, Vol.12 (8), p.1050

2023

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A Sensor-Based Perspective in Early-Stage Parkinson's Disease: Current State and the Need for Machine Learning Processes

Sensors (Basel, Switzerland), 2022-01, Vol.22 (2), p.409

2022

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Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution: A hybrid approach

Information sciences, 2012-12, Vol.216, p.50-92

2012

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Exploring Innovative Approaches to Synthetic Tabular Data Generation

Electronics (Basel), 2024-05, Vol.13 (10), p.1965

2024

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Machine Learning Analysis of Alzheimer’s Disease Single-Cell RNA-Sequencing Data across Cortex and Hippocampus Regions

Current issues in molecular biology, 2023-10, Vol.45 (11), p.8652-8669

2023

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Integromics network meta-analysis on cardiac aging offers robust multi-layer modular signatures and reveals micronome synergism

BMC genomics, 2015-03, Vol.16 (1), p.147-147, Article 147

2015

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Graph neural network approaches for single-cell data: a recent overview

Neural computing & applications, 2024-06, Vol.36 (17), p.9963-9987

2024

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Identifying Network Biomarkers for Alzheimer’s Disease Using Single-Cell RNA Sequencing Data

GeNeDis 2022, 2023, Vol.1423, p.207-214

2023

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Setting Up a Bio-AFM to Study Protein Misfolding in Neurodegenerative Diseases

GeNeDis 2022, 2023, Vol.1423, p.1-10

2023

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Challenges and limitations in computational prediction of protein misfolding in neurodegenerative diseases

Frontiers in computational neuroscience, 2024-01, Vol.17, p.1323182-1323182

2024

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CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis

Bioinformatics, 2016-03, Vol.32 (6), p.884-892

2016

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DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq experiments

Bioinformatics (Oxford, England), 2016-12, Vol.32 (24), p.3844-3846

2016

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Exploring Promising Biomarkers for Alzheimer’s Disease through the Computational Analysis of Peripheral Blood Single-Cell RNA Sequencing Data

Applied sciences, 2023-04, Vol.13 (9), p.5553

2023

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Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated “Omics” Approaches to Explore Measurable Metrics

Cancers, 2023-09, Vol.15 (17), p.4357

2023

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Emerging Machine Learning Techniques for Modelling Cellular Complex Systems in Alzheimer’s Disease

Advances in experimental medicine and biology, 2021-01, Vol.1338, p.199-208

2021

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Solving the linear interval tolerance problem for weight initialization of neural networks

Neural networks, 2014-06, Vol.54, p.17-37

2014

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Enhancing the Human Health Status Prediction: The ATHLOS Project

P72Inferring systems-level cardiac aging biomarkers through integromics network analysis

A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project

Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning

COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods

An Ensemble Feature Selection Approach for Analysis and Modeling of Transcriptome Data in Alzheimer’s Disease

Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

A Comparison of the Various Methods for Selecting Features for Single-Cell RNA Sequencing Data in Alzheimer’s Disease

A Network-Based Perspective in Alzheimer's Disease: Current State and an Integrative Framework

Assessing and Modelling of Post-Traumatic Stress Disorder Using Molecular and Functional Biomarkers

A Sensor-Based Perspective in Early-Stage Parkinson's Disease: Current State and the Need for Machine Learning Processes

Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution: A hybrid approach

Exploring Innovative Approaches to Synthetic Tabular Data Generation

Machine Learning Analysis of Alzheimer’s Disease Single-Cell RNA-Sequencing Data across Cortex and Hippocampus Regions

Integromics network meta-analysis on cardiac aging offers robust multi-layer modular signatures and reveals micronome synergism

Graph neural network approaches for single-cell data: a recent overview

Identifying Network Biomarkers for Alzheimer’s Disease Using Single-Cell RNA Sequencing Data

Setting Up a Bio-AFM to Study Protein Misfolding in Neurodegenerative Diseases

Challenges and limitations in computational prediction of protein misfolding in neurodegenerative diseases

CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis

DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq experiments

Exploring Promising Biomarkers for Alzheimer’s Disease through the Computational Analysis of Peripheral Blood Single-Cell RNA Sequencing Data

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated “Omics” Approaches to Explore Measurable Metrics

Emerging Machine Learning Techniques for Modelling Cellular Complex Systems in Alzheimer’s Disease

Solving the linear interval tolerance problem for weight initialization of neural networks

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