Loredana Bellantuono

Assistant Professor

University of Bari Aldo Moro

Italy

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Dr. Loredana Bellantuono is an Assistant Professor at the Università degli Studi di Bari Aldo Moro, Italy. Her research interests encompass artificial intelligence, explainable AI, socio-economic analyses, and complex networks, as evidenced by her recent publications. She has explored topics such as grokking in machine learning, socio-economic territorial biases in university rankings, and the impact of water pollution on antimicrobial resistance.

Articles (14)

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2025

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2025

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2025

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2023

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2023

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2023

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2022

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2022

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2022

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2022

Collaborators (11)

Roberto Cilli

Université de Lorraine

FRANCE

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Nicola Amoroso

Associate Professor

University of Bari Aldo Moro

ITALY

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Domenico Pomarico

University of Bari Aldo Moro

ITALY

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Roberto Bellotti

Professore Ordinario

University of Bari Aldo Moro

ITALY

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Antonio Lacalamita

University of Bari Aldo Moro

ITALY

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Alfonso Monaco

Istituto Nazionale di Fisica Nucleare

ITALY

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Giulio Pergola

ITALY

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Maricla Marrone

ITALY

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Luca Petruzzellis

University of Bari Aldo Moro

ITALY

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GIUSEPPE MAGNIFICO

Assistant Professor (RTDA)

ITALY

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Giancarlo Logroscino

Full Professor

University Aldo Moro

ITALY

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Loredana Bellantuono

Research Interests

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Articles (14)

Transfer Entropy and O-Information to Detect Grokking in Tensor Network Multi-Class Classification Problems

Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings

Measuring water pollution effects on antimicrobial resistance through explainable artificial intelligence

Detecting the socio-economic drivers of confidence in government with eXplainable Artificial Intelligence

Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions

Planck formula for the gluon parton distribution in the proton

Haemorrhage and Survival Times: Medical–Legal Evaluation of the Time of Death and Relative Evidence

TIRESIA: An eXplainable Artificial Intelligence Platform for Predicting Developmental Toxicity

The verbalization of numbers: An explainable framework for tourism online reviews

Artificial Intelligence and Complex Network Approaches Reveal Potential Gene Biomarkers for Hepatocellular Carcinoma

A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer’s Disease

Sustainable development goals: conceptualization, communication and achievement synergies in a complex network framework

The harmonium model and its unified system view of psychopathology: a validation study by means of a convolutional neural network

Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis

Collaborators (11)

Roberto Cilli

Nicola Amoroso

Domenico Pomarico

Roberto Bellotti

Antonio Lacalamita

Alfonso Monaco

Giulio Pergola

Maricla Marrone

Luca Petruzzellis

GIUSEPPE MAGNIFICO

Giancarlo Logroscino

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