5 papers · 1 filter
Geometry-Guided Generative Representation for Functional Brain Graphs
Subati Abulikemu, Tiago Azevedo, Michail Mamalakis +1
In network neuroscience, functional brain systems are often characterized using separate yet related graph-theoretic or spectral descriptors, overlooking how these properties covar…
Association-sensory spatiotemporal hierarchy and functional gradient-regularised recurrent neural network with implications for schizophrenia
Subati Abulikemu, Puria Radmard, Michail Mamalakis +1
The human neocortex is functionally organised at its highest level along a continuous sensory-to-association (AS) hierarchy. This study characterises the AS hierarchy of patients w…
Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods
Carmen Jimenez-Mesa, Yizhou Wan, Guilio Sansone +7
Brain tumor resection is a highly complex procedure with profound implications for survival and quality of life. Predicting patient outcomes is crucial to guide clinicians in balan…
The Explanation Necessity for Healthcare AI
Michail Mamalakis, Héloïse de Vareilles, Graham Murray +2
Explainability is a critical factor in enhancing the trustworthiness and acceptance of artificial intelligence (AI) in healthcare, where decisions directly impact patient outcomes.…
Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks
Michail Mamalakis, Antonios Mamalakis, Ingrid Agartz +4
The accelerated progress of artificial intelligence (AI) has popularized deep learning models across various domains, yet their inherent opacity poses challenges, particularly in c…