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Welcome to the 23rd International Conference on Artificial Intelligence in Medicine (AIME 2025) website. 

The AIME 2025 conference will be hosted by the University of Pavia, Italy on June 23-26, 2025.

During this special edition we will celebrate 40 years from the first AIME conference, held in Pavia in 1985.

AIME 2025 will offer the unique opportunity for researchers and other healthcare and AI experts to present significant theoretical, methodological and applied results related to the application of Artificial Intelligence (AI) in medicine.

Keynote Speakers

 

Silvana Quaglini

University of Pavia
Italy

Niels Peek

THIS Institute, DPHPC, University of Cambridge
United Kingdom

 

Bjoern Eskofier

MaD Lab, Friedrich-Alexander-Universität
Germany

 

Marinka Zitnik

Harvard Medical School
United States

KEY DATES

2024
1

OCTOBER

Submission opens
2025
27

JANUARY

Abstract submission deadline
2025
3
FEBRUARY
Paper submission deadline
2025

8

APRIL

Notification of acceptance
2025

20

APRIL
Camera-ready submission deadline
2025
23-26
JUNE
Main conference

PROGRAM

MONDAY
23
JUNE
TUESDAY
24
JUNE
WEDNESDAY
25
JUNE
THURSDAY
26
JUNE

DRAFT PROGRAM

  • MONDAY, JUNE 23RD 2025
  • 08:30 - 17:00
  • Room
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  • MAUGERI
  • 09:00 - 17:00
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  • MAUGERI
  • 17:30 - 20:00
  • AULA '400
  • UNIVERSITY OF PAVIA
  • TUESDAY, JUNE 24TH 2025
  • 9:00 - 10:20
  • Room
  • 9:00 - 9:20
  • PTransformer: A Prompt-based Multimodal Transformer Architecture For Medical Tabular Data
  • Yucheng Ruan, Xiang Lan, Daniel J. Tan, Hairil Rizal Abdullah and Mengling Feng
  • Room
  • 9:20 - 9:40
  • Leveraging Multi-Agent Systems for Domain-Pertinence Query Classification in Informative Chatbots
  • Patrizio Bellan, Saba Ghanbari Haez, Leonardo Sanna, Simone Magnolini and Mauro Dragoni
  • Room
  • 9:40 - 10:00
  • Elucidating mechanics of T cell signaling: Modelling surface receptor pathways using artificial neural networks
  • Julie Midroni, Duncan Kirby and Anton Zilman
  • Room
  • 10:00 - 10:20
  • Conformal Prediction for ECG Interpretation: A Study on Human-AI Collaboration in Clinical Decision Support
  • Duarte Folgado, Lorenzo Famiglini, Andrea Campagner, Hélder Dores, Marília Barandas, Hugo Gamboa and Federico Cabitza
  • Campus Medicine
  • 10:20 - 11:00
  • POSTER 1: Transformer-Based and LLM Architectures
  • Room
  • 10:20 - 11:00
  • Breast-CRAG: A Breast Cancer Large Language Model Leveraging Retrieval-Augmented Generation
  • Zikang Chen, Qinchuan Wang, Jinyan Liu, Yaoqian Sun, Heming Zheng, Haomin Li, Huilong Duan and Xudong Lu
  • A Fine-Tuning Pipeline with Small Conversational Data for Healthcare Chatbot
  • Gianluca Aguzzi, Matteo Magnini, Martino Francesco Pengo, Mirko Viroli and Sara Montagna
  • ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction
  • Aynur Guluzade, Naguib Heiba, Zeyd Boukhers, Florim Hamiti, Jahid Hasan Polash, Yehya Mohamad and Carlos A Velasco
  • Choose Your Words Wisely: Domain-adaptive Masking Makes Language Models Learn Faster
  • Vanshpreet S. Kohli, Aaron Monis and Radhika Mamidi
  • Exploring Large Language Model Reasoning Capabilities Over Personal Health Data
  • Gianluca Apriceno, Tania Bailoni and Mauro Dragoni
  • Enhancing RAGs for Rheumatology Triage: Strategies for Optimized Knowledge Retrieval
  • Tommaso Mario Buonocore, Emanuele Cardinale, Garifallia Sakellariou, Lucia Sacchi and Riccardo Bellazzi
  • Enhancing RAGAdvancing LOINC Mapping with AI: Insights from LARA’s RAG Implementation and Expert Evaluations for Rheumatology Triage: Strategies for Optimized Knowledge Retrieval
  • Alessandro Liscio, Maria Teresa Chiaravalloti, Vincenzo Giannattasio Dell'Isola and Monica Moz
  • Transformer-based Bi-encoder for Early Neonatal Birth Weight Prediction
  • Muhammad Mursil, Hatem A. Rashwan, Adnan Khalid, Luis Santos-Calderon, Pere Cavallé-Busquets, Michelle M. Murphy and Domenec Puig
  • Campus Medicine
  • 11:00 - 12:00
  • Room 1.8
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  • Campus Medicine
  • 12:00-13:00
  • Room
  • 12:00 - 12:20
  • AtGCN: A Lightweight Graph Convolutional Network for Ataxic Gait Detection
  • Karan Bania and Tanmay Verlekar
  • Room
  • 12:20 - 12:40
  • STM-GNN: space-time-and-memory graph neural networks for predicting multi-drug resistance risks in dynamic patient networks
  • Damien Geissbuhler, Alban Bornet, Catarina Marques, André Anjos, Sónia Pereira and Douglas Teodoro
  • Room
  • 12:40 - 13:00
  • A Graph Based Raman Spectral Processing Technique for Exosome Classification
  • Vuong Ngo, Edward Bolger, Stan Goodwin, John O'Sullivan, Dinh Viet Cuong and Mark Roantree
  • Campus Medicine
  • 13:00 - 14:30
  • Reinforcement Learning & Adaptive Decision Systems
  • Room
  • 13:00 - 13:30
  • Personalizing mHealth Apps with Offline Reinforcement Learning
  • Rutger van der Linden, Khadicha Amarti, Marketa Ciharova, Annet Kleiboer, Heleen Riper, Aneta Lisowska and Mark Hoogendoorn
  • Role-play Large Language Models for Short Behavior Change Interventions
  • Marco Bolpagni, Simone De Carli, Leonardo Sanna, Silvia Gabrielli and Mauro Dragoni
  • Probabilistic Modeling and Verification of an Adaptive VR Serious Game for Patients with Cognitive Impairment
  • Alessandro Forgiarini, Elisabetta De Maria and Fabio Buttussi
  • AI-Powered Care Robots for Compassionate Care: A Value-Sensitive Approach to Humanizing Healthcare
  • Elena Ricci, Paolo Dario, Gastone Ciuti, Michele Cardinali and Alberto Pirni
  • A Collaborative Learning Approach for Fairness in Prediction of Substance Use Disorder Treatment Completion
  • Mary Lucas and Christopher Yang
  • Developing a Dyslexia Indicator Using Eye Tracking
  • Kevin Cogan, Vuong Ngo and Mark Roantree
  • Physics-Informed Neural Networks for Hidden Insulin Dynamics Estimation from Glucose Data
  • Lea Multerer, Manuel Acquistapace, Marco Forgione and Laura Azzimonti
  • Advancing Deep Brain Stimulation: Machine Learning for Intraoperative SubThalamic Nucleus Targeting
  • Fabrizio Sciscenti, Valentina Agostini, Laura Rizzi, Michele Lanotte and Marco Ghislieri
  • Causal Inference, Counterfactuals, and Granger Analysis
  • Room
  • 13:30 - 14:00
  • Dynamic dose optimization under side effect constraints using counterfactual outcome prediction
  • Philipp Wendland and Maik Kschischo
  • LLM-guided Causal Bayesian Network construction for pediatric patients on ECMO
  • Saurabh Mathur, Ranveer Singh, Michael Skinner, Ethan Sanford, Neel Shah, Philip Reeder, Lakshmi Raman and Sriraam Natarajan
  • Causal Brain Connectivity: Integrating Granger Directed Graphs in fMRI Analysis
  • Tianyi Zhang, Keqi Han, Jiawei Nie, Chenyu You, Sanne van Rooij, Jennifer Stevens, Boadie Dunlop, Charles Gillespie and Carl Yang
  • Data-Driven Causal Discovery in Lifestyle Modeling
  • Radoslava Švihrová, Davide Marzorati, Alvise Dei Rossi, Tiziano Gerosa and Francesca Faraci
  • Domain-Adversarial Neural Networks to explore biases in the diagnosis of multiple eye conditions from fundus image data
  • Chiara Pullega, Arianna Dagliati and Allan Tucker
  • Who knocks on Heaven's door. Factors contributing to super-AI performance and human augmentation
  • Federico Cabitza
  • Reducing Total Fertilization Failure in In-Vitro Fertilization: A Prescriptive Analytics Framework
  • Shira Sadot, Tal Shavit and Nadav Rappoport
  • AI Models Predicting Methylation Status from DNA Sequence: What Is Missing?
  • Andrei Stefan Blindu, Silvia Berardelli, Federica De Paoli, Rossella Tricarico, Susanna Zucca and Paolo Magni
  • Generative Models
  • Room
  • 14:00 - 14:30
  • Pseudo-CT generation from uncorrected PET images using Multiview Ensemble Conditional Diffusion model
  • Alexandre St-Georges, Alexi Houle, Gabriel Richard, Maxime Toussaint, Étienne Auger, Christian Thibaudeau, Étienne Croteau, Stephen Cunnane, Roger Lecomte and Jean-Baptiste Michaud
  • Generating Novel Linker Sequences in Antibody-Drug Conjugates with Diffusion Models
  • April Cao and Jake Y. Chen
  • Upper Limb Movements Simulations with Generative Diffusion Models
  • Gabriele Santangelo, Chiara Alessi, Nikolas Sacchi, Giovanna Nicora, Riccardo Bellazzi, Antonella Ferrara and Arianna Dagliati
  • Physics-Informed CNN Ensemble for Improved Tissue Perfusion and Diffusion Estimation
  • Nicola Casali, Alessandro Brusaferri, Giuseppe Baselli, Stefano Fumagalli, Edoardo Micotti, Gianluigi Forloni, Riaz Hussein, Giovanna Rizzo and Alfonso Mastropietro
  • Unsupervised Deep Embedded Clustering Reveals High-Risk Subgroups for Alzheimer’s Disease
  • Coco Victoria Tirambulo, Simona Merlini, Carlos Lizarraga, Mithun Paul, Roberta Brinton and Francesca Vitali
  • Towards precision medicine with infrared molecular profiles: identifying and explaining subgroups
  • Lea Gigou, Kosmas V. Kepesidis and Ferenc Krausz
  • Unsupervised Assessment of Coronary Artery Tortuosity Through Hidden Markov Models
  • Michela Ferrari, Edoardo Spairani, Mario Urtis, Maurizia Grasso, Antonio Tescari, Eloisa Arbustini and Giovanni Magenes
  • Quality Assessment and Filtering of HE-stained Images for Machine Learning Applications
  • Daniela Pavlíková, Lucia Piatriková and Ivan Cimrák
  • Campus Medicine
  • 14:30 - 15:30
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  • Campus Medicine
  • 15:30 - 16:30
  • Room
  • 15:30 - 15:50
  • Causal Networks of Infodemiological Data: Modelling Dermatitis
  • Marco Scutari, Samir Salah, Delphine Kerob and Jean Krutmann
  • Room
  • 15:50 - 16:10
  • Counterfactual Inference Using Ordinary Differential Equations to Assess the Effect of Physical Activity on Type 2 Diabetes Onset
  • Marta Lenatti, Marco Zaffalon, Alessandro Antonucci, Pierluigi Francesco De Paola, Lea Multerer, Maurizio Mongelli, Alessia Paglialonga and Laura Azzimonti
  • Room
  • 16:10 - 16:30
  • A boxology-based analysis of design patterns for neuro-symbolic medical decision making systems
  • Chi Him Ng, Annette ten Teije and Frank van Harmelen
  • Campus Medicine
  • 16:30 - 17:00
  • POSTER 3: Graph-Based & Ontology-Based Methods
  • Room
  • 16:30 - 17:00
  • GraphNet: A novel method based on Graph Neural Networks for emergency healthcare management
  • Annamaria Defilippo, Pietro Hiram Guzzi, Pierangelo Veltri and Pietro Liò
  • Representing structured clinical databases through knowledge graphs: strategies and challenges with an application to MIMIC III dataset.
  • Beatrice Amico and Carlo Combi
  • Clinical outcome measurement scales: a domain ontology and a use case for stroke rehabilitation
  • Lucia Sacchi, Giovanna Nicora, Irene Giovanna Aprile and Silvana Quaglini
  • PGHDProvO: Provenance Based Ontology for Sharing Patient Generated Health Data (PGHD)
  • Abdullahi Abubakar Kawu, Dympna Osullivan and Lucy Hederman
  • Automated Phenotype-Based Clustering of Clinical Reports Using Large Language Models
  • Martina Saletta, Andrea Bombarda, Matteo Bellini, Lucrezia Goisis, Paolo Cazzaniga, Maria Iascone and Domenico Fabio Savo
  • Using Word Embeddings to Extract Semantic Relations from Biomedical Texts: Towards Literature-Based Discovery
  • William Van Woensel, Sushumna S. Pradeep, Ali Daowd, Samina Abidi and Syed Sibte Raza Abidi
  • AI-Driven Identification of Subclinical Alcohol Use Disorder in Type 2 Diabetes Patients
  • Melissa Larbi, Edouard Audit, Joel Chavas, Simplice Donfack and Vincent Mallet
  • Exploiting LLMs for Supporting Conformance Checking on Medical Processes
  • Giorgio Leonardi, Stefania Montani and Manuel Striani
  • Campus Medicine
  • 17:00 - 18:00
  • Room
  • 17:00 - 17:12
  • Surgical Instrument Segmentation and Self-Supervised Monocular Depth Estimation in Minimally Invasive Surgery: A Multi-task Learning Approach
  • Stefano Mazzocchetti, Laura Cercenelli and Emanuela Marcelli
  • Room
  • 17:12 - 17:24
  • Exploring the Use of Projecting Conflicting Gradients in Multi–Task Neural Networks with an Application to Amyotrophic Lateral Sclerosis
  • Davide Dei Cas, Enrico Longato, Erica Tavazzi, Umberto Manera, Adriano Chiò, Marta Gromicho, Inês Alves, Mamede De Carvalho and Barbara Di Camillo
  • Room
  • 17:24 - 17:36
  • Multi-Event Survival Analysis-Informed Clustering with MESA-LVQ: Functional System Worsening in Multiple Sclerosis
  • Robbe D'Hondt, Jasper de Boer and Celine Vens
  • Room
  • 17:36 - 17:48
  • Integration of infrared molecular fingerprinting data in a longitudinal health profiling cohort
  • Kosmas Kepesidis, Zita Zarandy, Flora Nemeth, Lea Gigou, Mihaela Zigman and Ferenc Krausz
  • Room
  • 17:48 - 18:00
  • FSLearning: An efficient Federated Split Learning Framework for Privacy-preserving Disease Prediction
  • Bin Li, Xiaoqian Jiang, Yu-Chun Hsu, Arif Harmanci, Hongchang Gao and Xinghua Shi
  • Campus Medicine
  • 17:00 - 18:00
  • Room
  • 17:00 - 17:12
  • Discovery of logic-probabilistic rules from COVID-19 vaccine antibody response in older people: results from the GeroCovid VAX Study
  • Michela Vespa, Francesca Remelli, Elena Bellodi and Raffaele Antonelli Incalzi
  • Room
  • 17:12 - 17:24
  • Unveiling Sleep Dysregulation in Chronic Fatigue Syndrome with and without Fibromyalgia Through Bayesian Networks
  • Michal Bechny, Marco Scutari, Julia van der Meer, Francesca Faraci, Benjamin Natelson and Akifumi Kishi
  • Room
  • 17:24 - 17:36
  • Machine Learning Approaches to the Early Detection of Pancreatic Cancer from Time-Series Primary Care Data
  • Victoria Moglia, Lesley Smith, Gordon Cook, Marc de Kamps and Owen Johnson
  • Room
  • 17:36 - 17:48
  • Machine Learning-Based Decision Support for Allergy Diagnosis: Real-World Implementation in a Hospital Setting
  • Paulina Tworek, Maja Szczypka, Julia Kahan, Marek Mikołajczyk, Roman Lewandowski and Jose Sousa
  • Room
  • 17:48 - 18:00
  • Enhancing Organ Transplant Outcomes: AI-Driven Prediction of Organ Viability Using Clinical Data
  • Pau Garre, Beatriz López, Núria Masnou and Guillem Guigó
  • Campus Medicine
  • 20:00
  • Social Dinner (pick up at 19:30)
  • Villa Botta Adorno
  • WEDNESDAY JUNE 25TH 2025
  • 9:00 - 10:20
  • Room
  • 09:00 - 09:20
  • Unsupervised domain adaptation for breast cancer detection in a multi-scanner environment: A case-study from Norway
  • Alba Ordonez, Fredrik Andreas Dahl, Olav Brautaset and Line Eikvil
  • Room
  • 09:20 - 09:40
  • Adaptive Clustering for EGFR Amplification Prediction in Glioblastoma: A Variational Autoencoder-Dirichlet Bayesian Gaussian Approach
  • Homay Danaei Mehr, Cong Cong, Imran Noorani, Antonio Di Ieva and Sidong Liu
  • Room
  • 09:40 - 10:00
  • A Reinforcement Learning Framework for Optimizing Kidney Allocation for Transplant Based on Survival and Ethical Criteria
  • Syed Asil Ali Naqvi, Karthik Tennankore, George Worthen, Amanda Vinson and Syed Sibte Raza Abidi
  • Room
  • 10:00 - 10:20
  • Reinforcement Learning for Hospital Outbreak Simulations
  • Denisse Kim, Guillermo Vigueras Gonzalez and Jose M. Juarez
  • Campus Medicine
  • 10:20 - 11:00
  • POSTER 4: Deep Learning applied to image analysis
  • Room
  • 10:20 - 11:00
  • Integrating Uncertainty into U-Net Robustness Evaluation under Natural MRI Alterations
  • Rossella Damiano, Elisa Scalco, Marco L. Della Vedova, Alberto Arrigoni, Anna Caroli, Andrea Bombarda and Ettore Lanzarone
  • AI-Based Mobile App for Segmentation and Tissue Classification in Diabetic Foot Ulcer
  • Adrián Jesús Maldonado Oclica, Regina Rios López, Adrián Emiliano Beltrán Fernández, Alexa Daniela Alquicira Guevara, Miguel Ángel Veloz Lucas, Andrés Rashid Abdul Flores Niño and María de Los Ángeles García Santiago
  • A Region-Specific GAN-Based Solution for Data Augmentation in Dermatology
  • Alessio Luschi, Linda Tognetti, Gabriele Cevenini, Pietro Rubegni and Ernesto Iadanza
  • Improved Allergy Wheal Detection for the Skin Prick Automated Test Device
  • Rembert Daems, Sven Seys, Valérie Hox, Adam Chaker, Glynnis De Greve, Winde Lemmens, Anne-Lise Poirrier, Eline Beckers, Zuzana Diamant, Carmen Dierickx, Peter W. Hellings, Caroline Huart, Claudia Jerin, Mark Jorissen, Hanne Oscé, Karolien Roux, Mark Thompson, Sophie Tombu, Saartje Uyttebroek, Andrzej Zarowski, Senne Gorris, Laura Van Gerven, Dirk Loeckx and Thomas Demeester
  • Review of Recent Deep Learning Techniques Using Longitudinal Mammogram Data
  • Aneta Gábrišová and Ivan Cimrák
  • Automated Instance Segmentation of Peripheral Nerve Microscopy Images
  • Krzysztof Spalinski, Antonina Spalinska, Michal Kopka, Paulina Przybylek, Magdalena Jasionowska-Skop and Artur Przelaskowski
  • Enhancing Diabetic Retinopathy Classification with Swin Transformer and Shifted Window Attention
  • Meher Boulaabi, Takwa Ben Aïcha Gader, Afef Kacem Echi and Zied Bouraoui
  • Explainable AI for Allergy Diagnosis: A CACTUS Framework to Address Doctor Variability
  • Luca Gherardini, Paulina Tworek, Maja Szczypka, Yousef Khan, Marek Mikołajczyk, Roman Lewandowski and Jose Sousa
  • Campus Medicine
  • 11:00 - 12:00
  • Room
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  • Campus Medicine
  • 12:00-13:00
  • Room
  • 12:00 - 12:12
  • Three-dimensional latent diffusion model for weakly-supervised brain tumour segmentation
  • Nico Loesch, Daniel R. Catchpoole and Paul J. Kennedy
  • Room
  • 12:12 - 12:24
  • Deep Learning driven Classification of Echocardiographic Apical Views: an approach based on Variational Autoencoders and Multilayer Perceptrons
  • Edoardo Spairani, Francesco Podda, Edoardo Bosco, Michela Ferrari, Marco Piastra, Giulia Matrone and Giovanni Magenes
  • Room
  • 12:24 - 12:36
  • Deep Spatial Context: When Attention-based Models Meet Spatial Regression (digital pathology)
  • Paulina Tomaszewska, Elżbieta Sienkiewicz, Mai P. Hoang and Przemysław Biecek
  • Room
  • 12:36 - 12:48
  • Augmentation-Free Contrastive Learning for EKG Classification
  • Junheng Wang and Milos Hauskrecht
  • Room
  • 12:48 - 13:00
  • fMRI Analysis for Alzheimer's Disease Detection: Traditional vs. Deep Learning Models
  • Adél Bajcsi and Camelia Chira
  • Campus Medicine
  • 12:00-13:00
  • Room
  • 12:00 - 12:12
  • Enriching Mental Health Chatbots using LLM-augmented State Machines: A Case Study on Self-Help+
  • Leonardo Sanna, Marco Bolpagni, Valentina Fietta, Giorgia Gavioli, Mattia Franzin, Mauro Dragoni and Silvia Gabrielli
  • Room
  • 12:12 - 12:24
  • Probing LLM Hidden States for Adverse Drug Reaction Knowledge
  • Jacob Berkowitz, Davy Weissenbacher, Apoorva Srinivasan, Nadine Friedrich, Jose Acitores Cortina, Sophia Kivelson, Graciela Gonzalez-Hernandez and Nicholas Tatonetti
  • Room
  • 12:24 - 12:36
  • Assessing GPT as a Weak Oracle for Annotating Radiological Studies
  • Joaquín De Ferrari, Domingo Benoit, Ricardo Ñanculef, Mauricio Araya and Mauricio Solar
  • Room
  • 12:36 - 12:48
  • Medical Prognosis from Electronic Health Records in Spanish
  • Nuria Lebena, Claudia Borg, Arantza Casillas and Alicia Pérez
  • Room
  • 12:48 - 13:00
  • Comparative Evaluation of Clinical Large Language Models and Machine Learning to Predict Antimicrobial Resistance in Hospital-Onset Sepsis
  • Scott A. Cohen, Ziyi Chen, Jiang Bian, Christina Boucher, Yonghui Wu and Mattia Prosperi
  • Campus Medicine
  • 13:00 - 14:30
  • Self-Supervised, Contrastive, and Representation Learning
  • Room
  • 13:00 - 13:30
  • Brugada Syndrome Diagnosis through Self-Supervised Contrastive Learning
  • Beatrice Zanchi, Giuliana Monachino, Luigi Fiorillo, Giulio Conte and Francesca Dalia Faraci
  • Contrasting by Augmented Patient Electrocardiograms to Learn Representations
  • Gul Rukh Khattak, Konstantinos Patlatzoglou, Yixiu Liang, Libor Pastika, Boroumand Zeidaabadi, Joseph Barker, Mehak Gurnani, Antonio H. Ribeiro, Jeffrey Annis, Antonio Luiz Pinho Ribeiro, Nicholas Peters, Junbo Ge, Daniel B. Kramer, Jonathan W. Waks, Evan Brittain, Arunashis Sau and Fu Siong Ng
  • MaCa: Mamba-Guided Causal Disentanglement for Breast Tumor Segmentation in Ultrasound Images
  • Haobo Chen, Changyan Wang and Qi Zhang
  • Reconstructing cycle-to-cycle ECG signal from Heart Sound
  • Balamurali B T, Prachee Priyadarshinee, Ivan Fu Xing Tan, Vern Hsen Tan, Siang Chew Chai, Colin Yeo and Jer-Ming Chen
  • Semi-Simulated Data for Improving Fetal QRS Detection using Deep Neural Networks
  • Giulio Steyde, Alessandra Galli, Andrea Cardinali, Edoardo Spairani, Giovanni Magenes and Maria G Signorini
  • Interpretable Early Detection of Parkinson’s Disease through Speech Analysis
  • Lorenzo Simone, Mauro Giuseppe Camporeale, Vito Marco Rubino, Giovanni Dimauro and Vincenzo Gervasi
  • From Regex to Encoders: Low-Effort Negation Detection for Healthcare Data Integration in Italian Hospitals
  • Tommaso Mario Buonocore, Sonia Mognaschi, Lorenzo Beretta, Serena Venturelli, Bruno Fattizzo, Eleonora Bruschi, Simone Benatti, Sara Marinoni, Chiara Cassani and Matteo Gabetta
  • Multi-Task Learning on Tabular Health Checkup Data for Prediction of Lifestyle-Related Diseases
  • Yuki Oba, Masaru Sanuki, Yukiko Wagatsuma and Taro Tezuka
  • Tabular, Traditional ML, and Ensemble Approaches
  • Room
  • 13:30 - 14:00
  • Machine Learning Predictions of Overall and Progression-Free Survival in Advanced Breast Cancer
  • Tatiana Merzhevich, Alexandros Tanzanakis, Emmanuelle Salin, Claudia Quiering, Benjamin Gmeiner, Bjoern Eskofier and Christoph Kurz
  • Predicting Length of Stay in Geriatric Patients Using an Ensemble Learning Method
  • Mariachiara Savino, Chiara Dachena, Carlotta Masciocchi, Stefania Orini, Roberto Gatta, Stefano Patarnello, Riccardo Rinaldi, Nicola Acampora, Eleonora Meloni, Giovanni Arcuri, Francesco Landi, Graziano Onder and Christian Barillaro
  • Predicting Intensive Care Unit Length of Stay in Pediatric Congenital Heart Disease Patients
  • Adriana Modrego, Esther Aurensanz, Julia Meca, Roger Domingo, Joan Sanchez-de-Toledo, Bart Bijnens and Patricia Garcia-Canadilla
  • Generalizability of AI survival models in the context of preterm birth prediction
  • Anne Fischer, Isabelle Dehaene and Mark Hoogendoorn
  • Development of falling detection AI model Using Neuro-Kinematic Multimodality in Parkinson
  • Min Kyung Kim, Myungjin Chung, Jinwhan Cho, Jinyoung Youn and Hakje Yoo
  • Machine Learning Models for Predicting Suicidal Ideation, Depression, Anxiety, and Stress in the General Population
  • Teodora Matić, Aleksander Sadikov, Peter Pregelj and Polona Rus Prelog
  • A Trustworthy Evolutionary Fuzzy Neural Network Framework for Maternal Health Risk Classification
  • Gianluca Apriceno, Marina Segala, Giovani Valer, Nicola Muraro, Vincenzo Netti, Paulo Vitor de Campos Souza and Mauro Dragoni
  • Using LSTM-based model on vocal signal analysis for the classification of multiple sclerosis
  • Muhammad Kashif, Patrizia Vizza, Aurora Delfino, Roberto Bruno Bossio, Giuseppe Tradigo, Sergio Flesca and Pierangelo Veltri
  • Evaluation, Explainability, Fairness, and Integration
  • Room
  • 14:00 - 14:30
  • Interpretable and explainable AI reveals EEG signatures of intervention in minimally conscious state patients
  • Davide Borra, Matteo Fraternali, Valentina Bonsangue, Susanna Lavezzi, Sofia Straudi and Elisa Magosso
  • Evaluating Large Language Models for Depression Symptom Estimation
  • Dhia Eddine Merzougui, Gaël Dias, Jeremie Pantin and Fabrice Maurel
  • Explainable AI for Smoking Behaviour Detection: A Danish Medical Records Study
  • Amir Sorayaie Azar, Margrethe Bang Høstgaard Henriksen, Ole Hilberg, Amin Naemi, Jamshid Bagherzadeh Mohasefi, Uffe Kock Will and Ali Ebrahimi
  • Do They Really Know? Evaluating Large Language Models’ Ability to Reference and Cite Oncology Guidelines
  • Pietro Belligoli, Danielle Bitterman and Timothy Miller
  • Towards Distributed Process Discovery in Healthcare: Testing and Proving the Feasibility of the Federated Alpha+ Algorithm
  • Leonardo Nucciarelli, Roberto Gatta, Andrada Mihaela Tudor, Erica Tavazzi, Giovanni Arcuri, Mauro Vallati, Gema Ibanez-Sanchez, Zoe Valero-Ramon, Carlos Fernández Llatas and Andrea Damiani
  • Enabling Transcriptome Classification in Micro-Cohorts with MLOps
  • Mahdieh Shabanian, Nima Pouladi, Liam Wilson, Mattia Prosperi and Yves Lussier
  • Deep learning approaches for prediction of mental and physical deterioration during chemotherapy
  • Joseph Finkelstein, Aref Smiley, Christina Echeverria and Kathi Mooney
  • Using Large language model for Efficient Extraction of Treatment Discontinuation Information
  • Qingyuan Song, Jessie Yang, Ndidiamaka Obi, Congning Ni, Jeremy Warner, Qingxia Chen, Lijun Song, Trent Rosenbloom, Bradley Malin and Zhijun Yin
  • Campus Medicine
  • 14:30 - 16:30
  • Room
  • 14:30 - 14:50
  • SHAP-FL: Improving Explainability for Multicentric Sepsis Onset Prediction Through Background Dataset Synthesis
  • Christoph Düsing and Philipp Cimiano
  • Room
  • 14:50 - 15:10
  • A SHAP Quotient Game for explaining Raman Spectroscopy classification models
  • Marco Piazza, Mauro Passacantando, Marzia Bedoni and Enza Messina
  • Room
  • 15:10 - 15:30
  • CUE-X: A Framework for the Automatic Evaluation of Clinical Usefulness of Explanations for the Multimorbidity Problem
  • Martin Michalowski, Szymon Wilk, Jenny Bauer, Marc Carrier and Wojtek Michalowski
  • Room
  • 15:30 - 15:50
  • Evaluating the Confidentiality of Synthetic Clinical Texts Generated by Language Models
  • Foucauld Estignard, Sahar Ghannay, Julien Girard-Satabin, Nicolas Hiebel and Aurélie Névéol
  • Room
  • 15:50 - 16:10
  • Balancing Fairness and Performance in Healthcare AI: A Gradient Projection Approach
  • Xiaoyang Wang and Christopher Yang
  • Room
  • 16:10 - 16:30
  • Evaluating the reporting quality of 21,041 randomized controlled trial articles with large language models: A large-scale transparency analysis
  • Apoorva Srinivasan, Sophia Kivelson, Nadine Friedrich, Jacob Berkowitz and Nicholas Tatonetti
  • Campus Medicine
  • 16:30 - 17:00
  • POSTER 6: DEMO
  • Room
  • 16:30 - 17:00
  • DBNcare: Towards an R Package for Dynamic Bayesian Networks Application in Healthcare
  • Francesco Canonaco, Federico Pirola and Fabio Stella
  • ML-EvalPro: Machine Learning Evaluation Profiler for Supervised Tasks
  • Mohamed Maher, Reem Ayman, Sondos Akram, Omar Marie and Radwa Elshawi
  • SFattolo: A Tool for Vignette-based Factorial Survey Management
  • Monica Consolandi, Jacopo Bennati, Alberto Cucino and Mauro Dragoni
  • DigiTher: an Open AI-based Platform for Digital Therapeutics Intervention
  • Claudio Eccher, Andrea Zorzi, Tania Bailoni, Stefania Poggianella and Mauro Dragoni
  • Generative AI meets genomics: VarChat, a RAG-based approach for literature-driven variant summarization
  • Federica De Paoli, Silvia Berardelli, Alessia Tudisco, Andrei Stefan Blindu, Enea Parimbelli and Susanna Zucca
  • BAT: A Toolkit for Biomedical Text Augmentation
  • Laura Bergomi, Enea Parimbelli, Daniele Pala and Tommaso Mario Buonocore
  • Data-Driven Demo Application For Adolescent Mental Health Screening With Decision Support
  • Dipendra Pant, Norbert Skokauskas, Bennett L. Leventhal, Thomas Brox Røst and Øystein Nytrø
  • Radiant: leveraging LLMs for Rare Disease research
  • Frank Hodges, Stephen Ramsey, Sundareswar Pullela, Jared Roach, Guy Cohen and Akshay Mulgund
  • Preventing Syringe Swap Errors with an Attention-Based CRNN: A Real-Time Mobile AI Solution
  • Patrick Reichherzer, Vanessa Restrepo Schild, Ollie Dare and Steven Webster-Edge
  • Campus Medicine
  • 17:00 - 18:00
  • Room
  • 17:00 - 17:12
  • An acoustic approach to confirm nasogastric tube placement
  • Charleen Yeo, Vijay Kevin Solomon, B T Balarumali, Saleem Ahmed, Jer-Ming Chen and Aaryan Nath Koura
  • Room
  • 17:12 - 17:24
  • Automated Movement Examination: Skeleton-based Human Action Recognition for Cognitive Impairment Detection
  • Abdul Moeed Siddiqui, Sayda Elmi and Morris Bell
  • Room
  • 17:24 - 17:36
  • Early Detection of ALS in Absence of Speech Impairments with Computer Audition
  • Adria Mallol-Ragolta, Monica Gonzalez-Machorro, Ricarda von Heynitz, Katia Scherzer, Isabell Cordts and Björn Schuller
  • Room
  • 17:36 - 17:48
  • Detection of ADHD from ECG Signals via Deep Learning-Based Feature Extraction
  • Xiaohan Li, Haiyan Xu, Yu Cao, Xudong Lu, Huilong Duan, Qiang Shu, Wei Wang and Haomin Li
  • Campus Medicine
  • 17:00 - 18:00
  • Room
  • 17:00 - 17:12
  • Graph Representation Learning for IBD diagnosis based on Microbiome Metaomic data
  • Christopher Irwin, Flavio Mignone, Stefania Montani and Luigi Portinale
  • Room
  • 17:12 - 17:24
  • A Graph Neural Network Approach for Data-Driven Donor-Recipient Matching in Kidney Transplantation
  • Sheida Majouni, Karthik Tennankore, Samina Abidi, Amanda Vinson and Syed Sibte Raza Abidi
  • Room
  • 17:24 - 17:36
  • Combining Clinical and Gene Expression Variables via Knowledge Graph Embedding for Prediction of Coronary Artery Stenosis
  • Giuseppe Albi, Arianna Dagliati, Chiara Vavassori, Laura Pisani, Mattia Chiesa, Luca Piacentini, Saima Mushtaq, Gianluca Pontone, Riccardo Bellazzi and Gualtiero I. Colombo
  • Room
  • 17:36 - 17:48
  • Reinforcement Learning on AYA Dyads to Enhance Medication Adherence
  • Ziping Xu, Hinal Jajal, Sung Won Choi, Inbal Nahum-Shani, Guy Shani, Alexandra Psihogios, Pei-Yao Hung and Susan Murphy
  • Room
  • 17:48 - 18:00
  • Explainable Machine Learning for Neonatal Screening: A Fast&Frugal Decision Tree for Rare Metabolic Disease Detection
  • Gloria Lopiano, Andrea Campagner, Cristina Cereda, Stephana Carelli and Federico Cabitza
  • Campus Medicine
  • 20:00
  • Social Dinner (pick up at 19:30)
  • Villa Botta Adorno
  • THURSDAY JUNE 26TH
  • 09:00 - 18:00
  • Room
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  • Maugeri/Campus Medicine
Pragma Congressi srl – Piazza Marelli 2 – 27100 Pavia – P.IVA 02031910181