“3rd AIxIA Workshop on Artificial Intelligence for Healthcare” and “5th Data4SmartHealth Workshop”

10:30: Opening – Room D1.03

• The opening ceremony

10:35: Keynote – Room D1.03

• Sara Montagna: Bridging AI and Healthcare: Trustworthy and Transparent Diagnostic Solutions with Informed Machine Learning

11:30: Medical Imaging and Anomaly Detection (MIAD) – Room D1.03

• L. Marconi, E. Pirovano and F. Cabitza: CLARITY AI: A Comprehensive Checklist Integrating Established Frameworks for Enhanced Research Quality in Medical AI Studies

• A. Marzullo and M. B. M. Ranzini: Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet?

• P. Bruno, A. Cirella, E. Di Cesare, G. Greco, A. Guzzo, P. Palumbo, S. J. Santini, G. Sinatti, P. Vittorini, C. Balsano and F. Calimeri: To Heart via Liver: a Study on Prognostic Stratification of Heart Disease in MASLD Patients using Machine Learning Models

• C. Dodaro, G. Galatà, M. Maratea, C. Marte and M. Mochi: Nuclear Medicine Rescheduling Problem: A Logic-based Approach

15:00: Working Group Meeting – Room D1.03

• Annual meeting of the AI and Healthcare Working Group of AIxIA

16:00: Minute Madness – Lightning Talks: short papers – Room D1.03

• A. Monaldini, A. Vozna and S. Costantini: Blueprint Personas in Digital Health Transformation

• E. De Rose, C. Adornetto, F. Calimeri and G. Greco: Features selection throught autoencoder filtering and DeepShap: an iterative algorithm

• L. Sanna, S. Magnolini, P. Bellan, S. Ghanbari Haez, M. Segala, M. Consolandi and M. Dragoni: Doctor, is it normal? Enabling medical chatbots to provide certified replies to normalcy questions

• J. Bolt, A. Berghuis, A. Hommersom, M. Lombaers, J. Pijnenborg and S. Renooij: Bayesian Networks in Medicine: Presenting Query Response Uncertainty for Decision Support

• L. Portinale, G. Leonardi and A. Santomauro: Similarity-based positional encoding for enhanced classification in medical images

• F. Angeli: An Educational Approach for Neurodiverse Children Using AI: A Case Study on DSA, Autism, and Dyscalculia

• M. Macrì, P. Bruno and C. Dodaro: Deep Learning Approaches for Segmentation and Classification of Breast Ultrasound Images

• P. Ribino, M. Mannone, C. Di Napoli, G. Paragliola, D. Chicco and F. Gasparini: Analyzing trajectories of clinical markers in patients with sepsis through multivariate longitudinal clustering

• A. Basile, F. Calefato, F. Lanubile, G. Logroscino, G. Mallardi and B. Tafuri: A Preliminary Study on Augmenting Neuroimaging data using a Diffusion Model

16:15: Minute Madness – Lightning Talks: non-original dissemination and discussion papers – Room D1.03

• B. Salvatori, S. Wegener, G. Kotzaeridi, A. Herding, F. Eppel, I. Dressler-Steinbach, W. Hernich, A. Piersanti, M. Morettini, A. Tura and C. Göbl: Identification and validation of gestational diabetes subgroups by data-driven cluster analysis

• B. Yousefi, F. Melograna, G. Galazzo, N. van Best, M. Mommers, J. Penders, B. Schwikowski and K. Van Steen: Capturing the dynamics of microbial interactions through individual-specific networks

• R. Khatun, S. Chatterjee, B. Christoph, M. Wadepohl, O. J. Ott, S. Semrau, R. Fietkau, A. Nürnberger, U. Gaipl and B. Frey: Complex-valued neural networks to speed-up MR Thermometry during Hyperthermia using Fourier PD and PDUNet

• Z. Li, F. Melograna, H. Hoskens, D. Duroux, M. Marazita, S. Walsh, S. Weinberg, M. Shriver, B. Müller-Myhsok, P. Claes and K. Van Steen: netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

• P. Bruno, F. Calimeri, F. Filice, C. Marte and S. Perri: IDADA: A Blended Inductive-Deductive Approach for Data Augmentation

• C. Radhakrishna, K. V. Chintalapati, S. C. H. Ram Kumar, R. Sutrave, H. Mattern, O. Speck, A. Nürnberger and S. Chatterjee: SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss

• C. Adornetto, P. Bruno, F. Calimeri, E. De Rose, G. Greco and A. Quarta: AI-Driven Innovations in Healthcare: Bridging Imaging and Genomics for Advanced Disease Insights

• A. Zanga, A. Bernasconi, P. J. F. Lucas, H. Pijnenborg, C. Reijnen, M. Scutari and A. C. Constantinou: Federated Causal Discovery with Missing Data in a Multicentric Study on Endometrial Cancer

• G. H. Bahre, H. Hamidi, A. Sellergren, L. A. Celi, F. Calimeri and L. Seyyed-Kalantari: Fairness Of AI Models in vector embedded Chest X-ray representations

16:30: Poster showcase and discussion – Room D1.03

All attendees are encouraged to directly and freely engage with the speakers, and open discussions and networking are explicitly fostered among the whole community.

10:30: Data4SmartHealth – Room D1.03 – See https://www.data4smarthealth.it for details.

• F. Boschello: AI based predicting tool for suicide attempts 

• D. Crazzolara: Can AI support the management of physical activity in people with type 1 diabetes?

• M. Farsad: Integrating AI in PET imaging for brain tumors

• M. Santarelli: AI-driven diagnosis and prediction: potential orthopedic clinical applications

13:30: Prognostic Models and Risk Assessment (PMRA) – part 1 – Room D1.03

• A. Calzoni, M. Savardi and A. Signoroni: Bimodal ECG-PCG Cardiovascular Disease Detection: a Close Look at Transfer Learning and Data Collection Issues

• A. Bernasconi, A. Balordi, A. Zanga and R. Cabañas: On Counterfactual Explainations of Cardiovascular Risk in Adolescents and Young Adults Breast Cancer Survivors

• G. Aguzzi, M. Magnini, S. Ferretti, G. P. Salcuni and S. Montagna: Applying Retrieval-Augmented Generation on Open LLMs for a Medical Chatbot Supporting Hypertensive Patients

14:15: Prognostic Models and Risk Assessment (PMRA) – part 2 – Room D1.03

• N. Rocchi, A. Bernasconi, A. Zanga, A. Gronchi, D. Callegaro, P. G. Casali, S. Provenzano, R. Miceli, A. Trama and F. Stella: A Causal Discovery Workflow for Rare Cancers: Case Study on Soft Tissue Sarcoma

• S. Ndlalane, O. Otegbeye and A. Ezugwu: Strategic Optimization of Blood Allocation in Blood Banks for Enhanced Resource Utilization

• G. Tinè and R. Miceli: A-MALA: A New Adaptive Version of the Metropolis Adjusted Langevin Algorithm for Survival Prediction in a High-Dimensional Framework

15:00: Techniques and Model Optimization (TMO) – Part 1 – Room D1.03

• V. V. N. K. C. Atkuri: Balancing Accuracy and Safety in AI: A Novel Adversarial Training Approach

• M. Locatelli, R. C. Cerioli, D. Besozzi, A. Hommersom and F. Stella: Reinforcement Learning and Fuzzy Logic Modelling for Personalized Dynamic Treatment

16:00: Techniques and Model Optimization (TMO) – Part 2 – Room D1.03

• T. Kolajo and O. Daramola: Predicting COVID-19 Post-vaccination Mortality in Persons with Cardiovascular Disease Risk Factors Using Explainable AI

• M. Serenelli, M. Quadrini, M. Óskarsdóttir and M. Loreti: Encoding Methods Comparison for Stress Detection

16:30: Clinical Decision Support and Digital Health (CDSDH) – part 1 – Room D1.03

• M. Dragoni, G. Apriceno and T. Bailoni: Validating a Functional Status Knowledge Graph in a Large-scale Living Lab

• S. Fazio, P. Ribino, F. Gasparini, N. Marwan, P. Fazio, M. Gherardi and M. Mannone: A physics-based view of brain-network alteration in neurological disease

• P. V. de Campos Souza and M. Dragoni: Artificial Intelligence in Emergency Care: Implementing Machine Learning for Triage Optimization in Italian Hospitals

17:15: Clinical Decision Support and Digital Health (CDSDH) – part 1 – Room D1.03

• M. Hosseinipour, L. Bergamin, H. Kotler, G. Gennaro and F. Aiolli: Addressing Challenges in Image Translation for Contrast-Enhanced Mammography using Generative Adversarial Networks

• F. de Arriba-Pérez and S. García-Méndez: Detecting anxiety and depression in dialogues: a multi-label and explainable approach

• M. Consolandi, S. Magnolini and M. Dragoni: Risk Communication in Healthcare: The Management of Misunderstandings

18:00: Awards Ceremony – Room D1.03

• Best Paper Award and Best Dissemination Award

18:10: Closing – Room D1.03

The closing ceremony.