Giovanna Maria Dimitri

Assistant Professor Tenure Track (RTT)

Università di Milano

Italy

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About

Giovanna Maria Dimitri is an Assistant Professor Tenure Track (RTT) at Università degli Studi di Milano, Italy. Her research areas include IoT and blockchain applications in agrifood supply chains, machine learning for health-related studies, and the analysis of multispectral satellite images. She has recently published articles on diverse topics such as organic food consumption, deep learning applications in medical imaging, and the interplay between brain and heart health.

Articles (10)

Year:

2025

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2025

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2024

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2022

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2022

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2022

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2022

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2022

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2021

Year:

2021

Collaborators (8)

Pietro Lio

Professor of Computational Biology

University of Cambridge

UNITED KINGDOM

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Maria Lucia Sampoli

Associate professor

Università degli Studi di Siena

ITALY

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Monica Bianchini

Università degli Studi di Siena

ITALY

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Claudio Schifanella

University of Turin

ITALY

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Alexander Kocian

Assistant Professor

University of Pisa

ITALY

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Gianluca brunori

full professor

University of Pisa

ITALY

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Claudio Luchinat

University of Florence

ITALY

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Stefano Chessa

Full Professor

University of Pisa

ITALY

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Giovanna Maria Dimitri

Research Interests

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About

Articles (10)

Interoperable Traceability in Agrifood Supply Chains: Enhancing Transport Systems Through IoT Sensor Data, Blockchain, and DataSpace

Analyzing the Impact of Organic Food Consumption on Citizens Health Using Unsupervised Machine Learning

A One-Class Classifier for the Detection of GAN Manipulated Multi-Spectral Satellite Images

Early downregulation of hsa-miR-144-3p in serum from drug-naïve Parkinson’s disease patients

NMR Spectroscopy Combined with Machine Learning Approaches for Age Prediction in Healthy and Parkinson’s Disease Cohorts through Metabolomic Fingerprints

Deep Learning Approaches for the Segmentation of Glomeruli in Kidney Histopathological Images

A Comparison of Machine Learning Approaches for Predicting Employee Attrition

A Short Survey on Deep Learning for Multimodal Integration: Applications, Future Perspectives and Challenges

A Mixed Statistical and Machine Learning Approach for the Analysis of Multimodal Trail Making Test Data

Modeling Brain–Heart Crosstalk Information in Patients with Traumatic Brain Injury

Collaborators (8)

Pietro Lio

Maria Lucia Sampoli

Monica Bianchini

Claudio Schifanella

Alexander Kocian

Gianluca brunori

Claudio Luchinat

Stefano Chessa

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