5 papers
RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis
Chris Tomy, Mo Vali, David Pertzborn +9
Histopathology, the current gold standard for cancer diagnosis, involves the manual examination of tissue samples after chemical staining, a time-consuming process requiring expert…
A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Transformer-Based Language Models
Michail Mamalakis, Tiago Azevedo, Cristian Cosentino +5
Interpretability remains a key challenge for deploying language models (LM) in clinical settings such as progression diagnosis of Alzheimer disease, where early and trustworthy pre…
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…
Artificial Intelligence-powered fossil shark tooth identification: Unleashing the potential of Convolutional Neural Networks
Andrea Barucci, Giulia Ciacci, Pietro Liò +7
All fields of knowledge are being impacted by Artificial Intelligence. In particular, the Deep Learning paradigm enables the development of data analysis tools that support subject…
New Insights on the Thermodynamic Equilibrium of Black Hole and Thermal Radiation
Ruifeng Zheng
The thermal balance between the black hole and surrounding thermal radiation is an interesting topic. The primordial black hole is a type of black hole formed in the early universe…