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ORCID23rd AIME 2025: Pavia, Italy - Part I
- Riccardo Bellazzi
, José Manuel Juarez Herrero, Lucia Sacchi, Blaz Zupan:
Artificial Intelligence in Medicine - 23rd International Conference, AIME 2025, Pavia, Italy, June 23-26, 2025, Proceedings, Part I. Lecture Notes in Computer Science 15734, Springer 2025, ISBN 978-3-031-95837-3 - Giuseppe Albi, Arianna Dagliati, Chiara Vavassori, Laura Pisani, Mattia Chiesa, Luca Piacentini, Saima Mushtaq, Gianluca Pontone, Riccardo Bellazzi, Gualtiero I. Colombo:
Combining Clinical and Gene Expression Variables via Knowledge Graph Embedding for Prediction of Coronary Artery Stenosis. 1-10 - Adél Bajcsi, Camelia Chira:
fMRI Analysis for Alzheimer's Disease Detection: Traditional vs. Deep Learning Models. 11-21 - Karan Bania, Tanmay Tulsidas Verlekar:
AtGCN: A Lightweight Graph Convolutional Network for Ataxic Gait Detection. 22-32 - Michal Bechny, Marco Scutari, Julia van der Meer, Francesca D. Faraci, Stéphane Meystre, Benjamin H. Natelson, Akifumi Kishi:
Unveiling Sleep Dysregulation in Chronic Fatigue Syndrome with and Without Fibromyalgia Through Bayesian Networks. 33-43 - Patrizio Bellan, Saba Ghanbari Haez, Leonardo Sanna, Simone Magnolini, Mauro Dragoni:
Leveraging Multi-agent Systems for Domain-Pertinence Query Classification in Informative Chatbots. 44-54 - Jacob S. Berkowitz, Davy Weissenbacher, Apoorva Srinivasan, Nadine A. Friedrich, Jose Miguel Acitores Cortina, Sophia Kivelson, Graciela Gonzalez-Hernandez, Nicholas P. Tatonetti:
Probing Large Language Model Hidden States for Adverse Drug Reaction Knowledge. 55-64 - Scott A. Cohen, Ziyi Chen, Jiang Bian, Christina Boucher, Yonghui Wu, Mattia Prosperi:
Comparative Evaluation of Clinical Large Language Models and Machine Learning to Predict Antimicrobial Resistance in Hospital-Onset Sepsis. 65-76 - Robbe D'hondt, Jasper de Boer, Celine Vens:
Multi-Event Survival-Informed Clustering for Time-to-Worsening in Multiple Sclerosis. 77-87 - Homay Danaei Mehr, Cong Cong, Imran Noorani, Antonio Di Ieva, Sidong Liu:
Adaptive Clustering for EGFR Amplification Prediction in Glioblastoma: A Variational Autoencoder-Dirichlet Bayesian Gaussian Approach. 88-97 - Joaquín De Ferrari, Ricardo Ñanculef, Domingo Benoit, Mauricio Araya, Mauricio Solar:
Assessing GPT as a Weak Oracle for Annotating Radiological Studies. 98-109 - Davide Dei Cas, Enrico Longato, Erica Tavazzi, Umberto Manera, Adriano Chiò, Marta Gromicho, Inês Alves, Mamede de Carvalho, Barbara Di Camillo:
Exploring the Use of Projecting Conflicting Gradients in Multi-task Neural Networks with an Application to Amyotrophic Lateral Sclerosis. 110-119 - Christoph Düsing, Philipp Cimiano:
SHAP-FL: Improving Explainability for Multicentric Sepsis Onset Prediction Through Background Dataset Synthesis. 120-129 - Foucauld Estignard, Sahar Ghannay, Julien Girard-Satabin, Nicolas Hiebel, Aurélie Névéol:
Evaluating the Confidentiality of Synthetic Clinical Texts Generated by Language Models. 130-139 - Duarte Folgado, Lorenzo Famiglini, Andrea Campagner, Hélder Dores, Marília Barandas, Hugo Gamboa, Federico Cabitza:
Conformal Prediction for ECG Interpretation: A Study on Human-AI Collaboration in Clinical Decision Support. 140-149 - Pau Garre, Beatriz López, Núria Masnou, Guillem Guigo:
Enhancing Organ Transplant Outcomes: AI-Driven Prediction of Organ Viability Using Clinical Data. 150-159 - Damien Geissbuhler, Alban Bornet, Catarina Marques, André Anjos, Sónia Pereira, Douglas Teodoro:
STM-GNN: Space-Time-and-Memory Graph Neural Networks for Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks. 160-169 - Christopher Irwin, Flavio Mignone, Stefania Montani, Luigi Portinale:
Graph Representation Learning for IBD Diagnosis Based on Microbiome Metaomic Data. 170-179 - Kosmas V. Kepesidis, Zita I. Zarandy, Flora B. Nemeth, Lea Gigou, Mihaela Zigman, Ferenc Krausz:
Integration of Infrared Molecular Fingerprinting Data in a Longitudinal Health Profiling Cohort. 180-190 - Denisse Kim, Guillermo Vigueras Gonzalez, Jose M. Juarez:
Reinforcement Learning for Hospital Outbreak Simulations. 191-201 - Nuria Lebeña, Claudia Borg, Arantza Casillas, Alicia Pérez:
Medical Prognosis from Electronic Health Records in Spanish. 202-211 - Marta Lenatti, Marco Zaffalon, Alessandro Antonucci, Pierluigi Francesco De Paola, Lea Multerer, Maurizio Mongelli, Alessia Paglialonga, Laura Azzimonti:
Counterfactual Inference Using Ordinary Differential Equations to Assess the Effect of Physical Activity on Type 2 Diabetes Onset. 212-221 - Bin Li, Xiaoqian Jiang, Yu-Chun Hsu, Arif Ozgun Harmanci, Hongchang Gao, Xinghua Shi:
FSLearning: An Efficient Federated Split Learning Framework for Privacy-Preserving Disease Prediction. 222-231 - Xiaohan Li, Haiyan Xu, Yu Cao, Xudong Lu, Huilong Duan, Qiang Shu, Wei Wang, Haomin Li:
Detection of ADHD from ECG Signals via Deep Learning-Based Feature Extraction. 232-241 - Nico Lösch, Daniel R. Catchpoole, Paul J. Kennedy:
Three-Dimensional Latent Diffusion Model for Weakly-Supervised Brain Tumour Segmentation. 242-251 - Gloria Lopiano, Andrea Campagner, Cristina Cereda, Stephana Carelli, Federico Cabitza:
Explainable Machine Learning for Neonatal Screening: A Fast&Frugal Decision Tree for Rare Metabolic Disease Detection. 252-261 - Sheida Majouni, Karthik K. Tennankore, Samina Abidi, Amanda Vinson, Syed Sibte Raza Abidi:
A Graph Neural Network Approach for Data-Driven Donor-Recipient Matching in Kidney Transplantation. 262-272 - Adria Mallol-Ragolta, Monica González Machorro, Ricarda von Heynitz, Katia Scherzer, Isabell Cordts, Björn W. Schuller:
Early Detection of ALS in Absence of Speech Impairments with Computer Audition. 273-282 - Stefano Mazzocchetti, Laura Cercenelli, Emanuela Marcelli:
Surgical Instrument Segmentation and Self-Supervised Monocular Depth Estimation in Minimally Invasive Surgery: A Multi-task Learning Approach. 283-292 - Martin Michalowski, Szymon Wilk, Jenny M. Bauer, Marc Carrier, Herna L. Viktor, Wojtek Michalowski:
CUE-X: A Framework for the Automatic Evaluation of Clinical Usefulness of Explanations for the Multimorbidity Problem. 293-303 - Julie Midroni, Duncan Kirby, Anton Zilman:
Elucidating Mechanics of T-cell Signaling: Modelling Surface Receptor Pathways Using Artificial Neural Networks. 304-312 - Victoria Moglia, Lesley Smith, Gordon Cook, Marc de Kamps, Owen A. Johnson:
Machine Learning Approaches to the Early Detection of Pancreatic Cancer from Time-Series Primary Care Data. 313-322 - Syed Asil Ali Naqvi, Karthik K. Tennankore, George Worthen, Amanda Vinson, Syed Sibte Raza Abidi:
A Reinforcement Learning Framework for Optimizing Kidney Allocation for Transplant Based on Survival and Ethical Criteria. 323-332 - Chi Him Ng, Annette ten Teije, Frank van Harmelen:
A Boxology-Based Analysis of Design Patterns for Neuro-Symbolic Medical Decision Making Systems. 333-343 - Vuong M. Ngo, Edward Bolger, Stan Goodwin, John O'Sullivan, Dinh Viet Cuong, Mark Roantree:
A Graph Based Raman Spectral Processing Technique for Exosome Classification. 344-354 - Alba Ordoñez, Fredrik A. Dahl, Olav Brautaset, Line Eikvil:
Unsupervised Domain Adaptation for Breast Cancer Detection in a Multi-Scanner Environment: A Case-Study from Norway. 355-364 - Marco Piazza, Mauro Passacantando, Marzia Bedoni, Enza Messina:
A SHAP Quotient Game for Explaining Raman Spectroscopy Classification Models. 365-374 - Yucheng Ruan, Xiang Lan, Daniel J. Tan, Hairil Rizal Abdullah, Mengling Feng:
PTransformer: A Prompt-Based Multimodal Transformer Architecture For Medical Tabular Data. 375-385 - Leonardo Sanna, Marco Bolpagni, Valentina Fietta, Giorgia Gavioli, Mattia Franzin, Mauro Dragoni, Silvia Gabrielli:
LLM-Enriched Finite-State Chatbots for Mental Health Support: A Case Study on Self-Help+. 386-396 - Marco Scutari, Samir Salah, Delphine Kerob, Jean Krutmann:
Causal Networks of Infodemiological Data: Modelling Dermatitis. 397-407 - Addul Moeed Siddiqui, Sayda Elmi, Morris Bell:
Automated Movement Examination: Skeleton-Based Human Action Recognition for Cognitive Impairment Detection. 408-417 - Francesco Podda, Edoardo Spairani, Edoardo Bosco, Michela Ferrari, Marco Piastra, Giulia Matrone, Giovanni Magenes:
Deep Learning Driven Classification of Echocardiographic Apical Views: An Approach Based on Variational Autoencoders and Multilayer Perceptrons. 418-427 - Apoorva Srinivasan, Sophia Kivelson, Nadine A. Friedrich, Jacob S. Berkowitz, Nicholas P. Tatonetti:
Evaluating the Reporting Quality of 21,041 Randomized Controlled Trial Articles with Large Language Models: A Large-Scale Transparency Analysis. 428-437 - Paulina Tomaszewska, Elzbieta Sienkiewicz, Mai P. Hoang, Przemyslaw Biecek:
Deep Spatial Context: When Attention-Based Models Meet Spatial Regression (Digital Pathology). 438-447 - Paulina Tworek, Maja Szczypka, Julia Kahan, Marek Mikolajczyk, Roman Lewandowski, José L. R. Sousa:
Machine Learning-Based Decision Support for Allergy Diagnosis: Real-World Implementation in a Hospital Setting. 448-456 - Michela Vespa, Francesca Remelli, Elena Bellodi, Raffaele Antonelli Incalzi:
Discovery of Logic-Probabilistic Rules from COVID-19 Vaccine Antibody Response in Older People: Results from the GeroCovid VAX Study. 457-467 - Junheng Wang, Milos Hauskrecht:
Augmentation-Free Contrastive Learning for EKG Classification. 468-479 - Xiaoyang Wang, Christopher C. Yang:
Balancing Fairness and Performance in Healthcare AI: A Gradient Reconciliation Approach. 480-489 - Ziping Xu, Hinal Jajal, Sung Won Choi, Inbal Nahum-Shani, Guy Shani, Alexandra M. Psihogios, Pei-Yao Hung, Susan A. Murphy:
Reinforcement Learning on Dyads to Enhance Medication Adherence. 490-499 - Charleen Yeo, Vijay Kevin Solomon, Balamurali B. T., Saleem Ahmed, Chen Jer-Ming, Koura Aaryan Nath:
An Acoustic Approach to Confirm Nasogastric Tube Placement. 500-509
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