12 citations · 28 across the 11 of their papers we have counts for
11 papers
EchoRisk: A Multicentre Echocardiography Dataset and Benchmark for Cardio-Oncology
Grigorios Kalliatakis, Georgia Karanasiou, Georgios Manikis +10
Therapy-induced cardiotoxicity is the leading non-oncological cause of treatment interruption in breast cancer patients, yet early, automated risk stratification from routine cardi…
TDGT: A Tabular Data Generation Toolkit supporting adaptive GPU-accelerated Bayesian mixture models, diffusion-based models, and latent-space generative modeling
Vasileios C. Pezoulas, Nikolaos S. Tachos, Eleni Georga +3
The growing demand for privacy-preserving data sharing has positioned synthetic data generation as a critical component of responsible AI workflows. Despite notable advances in gen…
Stress Estimation in Elderly Oncology Patients Using Visual Wearable Representations and Multi-Instance Learning
Ioannis Kyprakis, Vasileios Skaramagkas, Georgia Karanasiou +10
Psychological stress is clinically relevant in cardio-oncology, yet it is typically assessed only through patient-reported outcome measures (PROMs) and is rarely integrated into co…
Frailty Estimation in Elderly Oncology Patients Using Multimodal Wearable Data and Multi-Instance Learning
Ioannis Kyprakis, Vasileios Skaramagkas, Georgia Karanasiou +10
Frailty and functional decline strongly influence treatment tolerance and outcomes in older patients with cancer, yet assessment is typically limited to infrequent clinic visits. W…
Synthetic Data Blueprint (SDB): A modular framework for the statistical, structural, and graph-based evaluation of synthetic tabular data
Vasileios C. Pezoulas, Nikolaos S. Tachos, Eleni Georga +3
In the rapidly evolving era of Artificial Intelligence (AI), synthetic data are widely used to accelerate innovation while preserving privacy and enabling broader data accessibilit…
Efficient Pain Recognition via Respiration Signals: A Single Cross-Attention Transformer Multi-Window Fusion Pipeline
Stefanos Gkikas, Ioannis Kyprakis, Manolis Tsiknakis
Pain is a complex condition that affects a large portion of the population. Accurate and consistent evaluation is essential for individuals experiencing pain and supports the devel…
Multi-Representation Diagrams for Pain Recognition: Integrating Various Electrodermal Activity Signals into a Single Image
Stefanos Gkikas, Ioannis Kyprakis, Manolis Tsiknakis
Pain is a multifaceted phenomenon that affects a substantial portion of the population. Reliable and consistent evaluation supports individuals experiencing pain and enables the de…
Tiny-BioMoE: a Lightweight Embedding Model for Biosignal Analysis
Stefanos Gkikas, Ioannis Kyprakis, Manolis Tsiknakis
Pain is a complex and pervasive condition that affects a significant portion of the population. Accurate and consistent assessment is essential for individuals suffering from pain,…
AI Model Passport: Data and System Traceability Framework for Transparent AI in Health
Varvara Kalokyri, Nikolaos S. Tachos, Charalampos N. Kalantzopoulos +10
The increasing integration of Artificial Intelligence (AI) into health and biomedical systems necessitates robust frameworks for transparency, accountability, and ethical complianc…
PainFormer: a Vision Foundation Model for Automatic Pain Assessment
Stefanos Gkikas, Raul Fernandez Rojas, Manolis Tsiknakis
Pain is a manifold condition that impacts a significant percentage of the population. Accurate and reliable pain evaluation for the people suffering is crucial to developing effect…
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging
Karim Lekadir, Richard Osuala, Catherine Gallin +13
The recent advancements in artificial intelligence (AI) combined with the extensive amount of data generated by today's clinical systems, has led to the development of imaging AI s…