HC@AIXIA 2023: 2ND AIXIA WORKSHOP ON ARTIFICIAL INTELLIGENCE FOR HEALTHCARE (HC@AIXIA 2023)

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Albusac, Javier	Decision support system for automatic adjustment of rehabilitation routines for stroke patients
Aprile, Alessandro	A Federated Learning Framework for Stenosis Detection
Archetti, Alberto	Deep Survival Analysis for Healthcare: An Empirical Study on Post-Processing Techniques
Aricò, Pietro	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Avolio, Matteo	Viral pneumonia images classification by Multiple Instance Learning: preliminary results.
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Babiloni, Fabio	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Bajaj, Himanshi	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent
Bellazzi, Riccardo	Evaluation of Machine Learning Predictions’ Reliability with generative models: towards Trustworthy AI
Bellocchio, Francesco	Clinical Intervention Effectiveness Estimation through Dynamic Bayesian Network
Benedetti, Riccardo	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Bernasconi, Alice	Towards a Transportable Causal Network Model Based on Observational Healthcare Data
Bernasconi, Alice	The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Bertoncelli, Carlo Maria	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
Bertoncelli, Domenico	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
Biancucci, Federica	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Boccato, Tommaso	Brain Captioning: Decoding human brain Activity into images and text Breaking the Structure of Multilayer Perceptrons with Complex Topologies
Bogliolo, Alessandro	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Borghini, Gianluca	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Bregoli, Alessandro	Clinical Intervention Effectiveness Estimation through Dynamic Bayesian Network
Bruno, Pierangela	Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming
C
Cabrio, Elena	On the Automatic Assessment of Natural Language Expert Explanations in Medicine
Calimeri, Francesco	Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming
Cangelosi, Davide	Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction
Caruso, Simone	Scheduling Periodic Treatments via Answer Set Programming
Castro-Schez, José J.	Decision support system for automatic adjustment of rehabilitation routines for stroke patients
Chatterjee, Soumick	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent Sinogram upsampling using Primal–Dual UNet for undersampled CT and radial MRI reconstruction
Chicco, Davide	Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction
Ciardiello, Andrea	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
Collias, Theo Alkibiades	On the Automatic Assessment of Natural Language Expert Explanations in Medicine
Costantini, Stefania	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
Cremonini, Francesca	A Novel Cephalometric Tool Enhanced by AI Assistance
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D'Amore, Nunzio	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
De Maio, Matteo	A Novel Cephalometric Tool Enhanced by AI Assistance
De Meo, Pasquale	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
Di Cosmo, Mariachiara	A Federated Learning Framework for Stenosis Detection
Di Floro, Antonio	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Di Flumeri, Gianluca	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Di Napoli, Claudia	Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques
Dodaro, Carmine	Scheduling Periodic Treatments via Answer Set Programming
Donati, Matteo	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Dossena, Marco	Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring
Duggento, Andrea	Breaking the Structure of Multilayer Perceptrons with Complex Topologies
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Ernst, Philipp	Sinogram upsampling using Primal–Dual UNet for undersampled CT and radial MRI reconstruction
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Falcone, Rino	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
Ferrante, Matteo	Brain Captioning: Decoding human brain Activity into images and text
Ferrante, Matteo	Breaking the Structure of Multilayer Perceptrons with Complex Topologies
Ferretti, Stefano	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Fiorentino, Maria Chiara	A Federated Learning Framework for Stenosis Detection
Francioni, Matteo	A Federated Learning Framework for Stenosis Detection
Frontoni, Emanuele	A Federated Learning Framework for Stenosis Detection
Fuduli, Antonio	Viral pneumonia images classification by Multiple Instance Learning: preliminary results.
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Galatà, Giuseppe	Scheduling Periodic Treatments via Answer Set Programming Master Surgical Scheduling via Answer Set Programming tested on real data
Garaventa, Alberto	Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction
Gargiulo, Simona	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
Gasparini, Francesca	Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques
Germano, Daniele	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Giagu, Stefano	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
Giorgi, Andrea	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Gmez-Portes, Cristian	Decision support system for automatic adjustment of rehabilitation routines for stroke patients
Grillo, Greta	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
H
Haupt, Riccardo	Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction
Herrera, Vanesa	Decision support system for automatic adjustment of rehabilitation routines for stroke patients
I
Irwin, Christopher	Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring
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Leonardi, Giorgio	Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring Enhancing Medical Image Report Generation through Standard Language Models: Leveraging the Power of LLMs in Healthcare
Lombardo, Luca	A Novel Cephalometric Tool Enhanced by AI Assistance
Lucas, Peter J. F.	Towards a Transportable Causal Network Model Based on Observational Healthcare Data The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Luksch, Roberto	Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction
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Magnani, Mauro	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Maolo, Alessandro	A Federated Learning Framework for Stenosis Detection
Maratea, Marco	Scheduling Periodic Treatments via Answer Set Programming Master Surgical Scheduling via Answer Set Programming tested on real data
Marro, Santiago	On the Automatic Assessment of Natural Language Expert Explanations in Medicine
Marte, Cinzia	Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming
Martínez, Sergio	Decision support system for automatic adjustment of rehabilitation routines for stroke patients
Matteucci, Matteo	Deep Survival Analysis for Healthcare: An Empirical Study on Post-Processing Techniques
Menghini, Igor	AI in healthcare: A view from the industry
Menotta, Michele	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Migliorelli, Giovanna	A Federated Learning Framework for Stenosis Detection
Moccia, Sara	A Federated Learning Framework for Stenosis Detection
Mochi, Marco	Master Surgical Scheduling via Answer Set Programming tested on real data
Montagna, Sara	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Montani, Stefania	Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring
Mucaj, Andi	A Federated Learning Framework for Stenosis Detection
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Neri, Luca	Clinical Intervention Effectiveness Estimation through Dynamic Bayesian Network
Nicolina, Sciaraffa	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Nicora, Giovanna	Evaluation of Machine Learning Predictions’ Reliability with generative models: towards Trustworthy AI
Nürnberger, Andreas	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent Sinogram upsampling using Primal–Dual UNet for undersampled CT and radial MRI reconstruction
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Paragliola, Giovanni	Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques
Peracchio, Lorenzo	Evaluation of Machine Learning Predictions’ Reliability with generative models: towards Trustworthy AI
Perri, Simona	Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming
Persia, Fabio	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
Pijnenborg, Johanna	The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Portinale, Luigi	Enhancing Medical Image Report Generation through Standard Language Models: Leveraging the Power of LLMs in Healthcare
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Reijnen, Casper	The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Ribino, Patrizia	Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques
Ronca, Vincenzo	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
Rose, Georg	Sinogram upsampling using Primal–Dual UNet for undersampled CT and radial MRI reconstruction
Rossi, Silvia	The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem
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Santomauro, Andrea	Enhancing Medical Image Report Generation through Standard Language Models: Leveraging the Power of LLMs in Healthcare
Scardapane, Simone	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
Scutari, Marco	Towards a Transportable Causal Network Model Based on Observational Healthcare Data The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Serino, Luca	Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques
Shashidhar, Suraj Bangalore	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent
Siddiquee, Istiyak H.	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent
Simon, Steve	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent
Sirocchi, Christel	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
Speck, Oliver	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent Sinogram upsampling using Primal–Dual UNet for undersampled CT and radial MRI reconstruction
Stella, Fabio A.	Towards a Transportable Causal Network Model Based on Observational Healthcare Data The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Stranieri, Francesco	Deep Survival Analysis for Healthcare: An Empirical Study on Post-Processing Techniques
Subbarayappa, Nandish Bandi	MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent
Suffian, Muhammad	Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders
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Tamascelli, Michael	A Novel Cephalometric Tool Enhanced by AI Assistance
Torda, Tommaso	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
Toschi, Nicola	Brain Captioning: Decoding human brain Activity into images and text
Toschi, Nicola	Breaking the Structure of Multilayer Perceptrons with Complex Topologies
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Usvyat, Len	Clinical Intervention Effectiveness Estimation through Dynamic Bayesian Network
Uva, Paolo	Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction
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Vallejo, David	Decision support system for automatic adjustment of rehabilitation routines for stroke patients
Villata, Serena	On the Automatic Assessment of Natural Language Expert Explanations in Medicine
Vocaturo, Eugenio	Viral pneumonia images classification by Multiple Instance Learning: preliminary results.
Voena, Cecilia	Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach
Vozzi, Alessia	Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces
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Zanga, Alessio	Towards a Transportable Causal Network Model Based on Observational Healthcare Data The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study
Zese, Riccardo	A Novel Cephalometric Tool Enhanced by AI Assistance
Zumpano, Ester	Viral pneumonia images classification by Multiple Instance Learning: preliminary results.

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