Pietro Bosoni

Orcid: 0000-0002-1431-6044

According to our database1, Pietro Bosoni authored at least 28 papers between 2016 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
The association of environmental exposure with multiple sclerosis severity score: A study based on sequential data modeling.
Int. J. Medical Informatics, 2026

2025

Longitudinal Missing Data Imputation for Predicting Disability Stage of Patients with Multiple Sclerosis.
CoRR, January, 2025

Temporal Characterization of Glycemia Risk Index Sequences through Random Walk Bayesian Clustering.
Proceedings of the 13th IEEE International Conference on Healthcare Informatics, 2025

Effect of Environmental Personal Exposure on Amyotrophic Lateral Sclerosis Disease Progression.
Proceedings of the 13th IEEE International Conference on Healthcare Informatics, 2025

Deep Learning Model Predicts Relapse Occurrence in Multiple Sclerosis Via Sequences of Environmental Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2025

2024


Smartphone applications for nutrition Support: A systematic review of the target outcomes and main functionalities.
Int. J. Medical Informatics, 2024

Domain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries.
CoRR, 2024

Exploring the Impact of Environmental Pollutants on Multiple Sclerosis Progression.
CoRR, 2024

Forecasting glucose values for patients with type 1 diabetes using heart rate data.
Comput. Methods Programs Biomed., 2024

Continuous Markov Models for Analyzing the Effect of Environmental Personal Exposure on Multiple Sclerosis Progression.
Proceedings of the pHealth 2024 - Proceedings of the 20th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2024

Predicting Multiple Sclerosis Relapses Using Patient Exposure Trajectories.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024), 2024



NutriA: a Responsive Web App to Monitor Nutrition and Clinical Outcomes in Inflammatory Bowel Disease Patients.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

Land Use Regression on Interpolated Urban Graphs to Assess Personal Exposure to Air Pollution.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

Machine Learning Models Highlight the Impact of Pollution and Weather Patterns on Relapse Occurrence in Multiple Sclerosis Patients.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

Assessing a Personalized, Hybrid, and Generic Approach for Glucose Prediction in Type 1 Diabetes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023
V-care: An application to support lifestyle improvement in children with obesity.
Int. J. Medical Informatics, September, 2023

Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review.
Artif. Intell. Medicine, August, 2023

Predicting and Explaining Risk of Disease Worsening Using Temporal Features in Multiple Sclerosis.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), 2023

2020
Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform.
Sensors, 2020

Deep Learning Applied to Blood Glucose Prediction from Flash Glucose Monitoring and Fitbit Data.
Proceedings of the Artificial Intelligence in Medicine, 2020

2019
Latent Class Multi-Label Classification to Identify Subclasses of Disease for Improved Prediction.
Proceedings of the 32nd IEEE International Symposium on Computer-Based Medical Systems, 2019

2018
Nearest Consensus Clustering Classification to Identify Subclasses and Predict Disease.
J. Heal. Informatics Res., 2018

2016
Combining Unsupervised and Supervised Learning for Discovering Disease Subclasses.
Proceedings of the 29th IEEE International Symposium on Computer-Based Medical Systems, 2016


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