AWARDS

The Program Committee of HC@AIxIA 2023 is proud to present two distinct awards: one is granted to the best among all ORIGINAL works accepted to the workshop, while the other is awarded to the work that best communicates recent important results, possibly with an interdisciplinary character. The recipients of the two award are reported next.

List of Accepted Papers

Original Papers

• Christel Sirocchi, Federica Biancucci, Matteo Donati, Nunzio D'Amore, Riccardo Benedetti, Alessandro Bogliolo, Stefano Ferretti, Mauro Magnani, Michele Menotta, Muhammad Suffian and Sara Montagna. Machine Learning-Enabled Prediction of Metabolite Response in Genetic Disorders

• Alessandro Bregoli, Luca Neri, Len Usvyat and Francesco Bellocchio. Clinical Intervention Effectiveness Estimation through Dynamic Bayesian Network

• Tommaso Torda, Simona Gargiulo, Greta Grillo, Andrea Ciardiello, Cecilia Voena, Stefano Giagu and Simone Scardapane. Tracin in Semantic Segmentation of tumor brains in MRI, an extended approach

• Riccardo Zese, Luca Lombardo, Matteo De Maio, Michael Tamascelli and Francesca Cremonini. A Novel Cephalometric Tool Enhanced by AI Assistance

• Christopher Irwin, Marco Dossena, Giorgio Leonardi and Stefania Montani. Structural Positional Encoding for knowledge integration in transformer-based medical process monitoring

• Andrea Santomauro, Luigi Portinale and Giorgio Leonardi. Enhancing Medical Image Report Generation through Standard Language Models: Leveraging the Power of LLMs in Healthcare

• Sergio Martínez, Cristian Gmez-Portes, Vanesa Herrera, Javier Albusac, José J. Castro-Schez and David Vallejo. Decision support system for automatic adjustment of rehabilitation routines for stroke patients

• Alice Bernasconi, Alessio Zanga, Peter J. F. Lucas, Marco Scutari and Fabio A. Stella. Towards a Transportable Causal Network Model Based on Observational Healthcare Data

• Santiago Marro, Theo Alkibiades Collias, Elena Cabrio and Serena Villata. On the Automatic Assessment of Natural Language Expert Explanations in Medicine

• Alberto Archetti, Francesco Stranieri and Matteo Matteucci. Deep Survival Analysis for Healthcare: An Empirical Study on Post-Processing Techniques

• Patrizia Ribino, Claudia Di Napoli, Giovanni Paragliola, Luca Serino, Francesca Gasparini and Davide Chicco. Exploratory analysis of longitudinal data of patients with dementia through unsupervised techniques

• Giuseppe Galatà, Marco Maratea and Marco Mochi. Master Surgical Scheduling via Answer Set Programming tested on real data

• Stefania Costantini, Fabio Persia, Pasquale De Meo, Silvia Rossi, Rino Falcone, Carlo Maria Bertoncelli and Domenico Bertoncelli. The PredictMed-POMAS Architecture for Intelligent Patient Monitoring within a Complex Healthcare Ecosystem

Non-original Contributions

• Matteo Ferrante, Tommaso Boccato and Nicola Toschi. Brain Captioning: Decoding human brain Activity into images and text

• Lorenzo Peracchio, Giovanna Nicora and Riccardo Bellazzi. Evaluation of Machine Learning Predictions’ Reliability with generative models: towards Trustworthy AI

• Pierangela Bruno, Francesco Calimeri, Cinzia Marte and Simona Perri. Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming

• Simone Caruso, Carmine Dodaro, Giuseppe Galatà and Marco Maratea. Scheduling Periodic Treatments via Answer Set Programming

• Philipp Ernst, Soumick Chatterjee, Georg Rose, Oliver Speck and Andreas Nürnberger. Sinogram upsampling using Primal–Dual UNet for undersampled CT and radial MRI reconstruction

• Soumick Chatterjee, Himanshi Bajaj, Istiyak H. Siddiquee, Nandish Bandi Subbarayappa, Steve Simon, Suraj Bangalore Shashidhar, Oliver Speck and Andreas Nürnberger. MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent

• Mariachiara Di Cosmo, Giovanna Migliorelli, Matteo Francioni, Andi Mucaj, Alessandro Aprile, Alessandro Maolo, Emanuele Frontoni, Maria Chiara Fiorentino and Sara Moccia. A Federated Learning Framework for Stenosis Detection

• Davide Chicco, Riccardo Haupt, Alberto Garaventa, Paolo Uva, Roberto Luksch and Davide Cangelosi. 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

• Alessio Zanga, Alice Bernasconi, Peter Lucas, Johanna Pijnenborg, Casper Reijnen, Marco Scutari and Fabio Stella. The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study

• Eugenio Vocaturo, Matteo Avolio, Antonio Fuduli and Ester Zumpano. Viral pneumonia images classification by Multiple Instance Learning: preliminary results

• Sciaraffa Nicolina, Gianluca Di Flumeri, Daniele Germano, Andrea Giorgi, Antonio Di Floro, Gianluca Borghini, Alessia Vozzi, Vincenzo Ronca, Fabio Babiloni and Pietro Aricò. Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces

• Tommaso Boccato, Matteo Ferrante, Andrea Duggento and Nicola Toschi. Breaking the Structure of Multilayer Perceptrons with Complex Topologies