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Found 5 papers, 1 papers with code
Multimodal Learning To Improve Cardiac Late Mechanical Activation Detection From Cine MR Images
This paper presents a multimodal deep learning framework that utilizes advanced image techniques to improve the performance of clinical analysis heavily dependent on routinely acquired standard images.
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces
To achieve this, we develop a neural operator that for the first time learns the evolving trajectory of geodesic deformations parameterized in the tangent space of diffeomorphisms(a. k. a velocity fields).
From Static to Dynamic Structures: Improving Binding Affinity Prediction with a Graph-Based Deep Learning Model
Accurate prediction of the protein-ligand binding affinities is an essential challenge in the structure-based drug design.
Hybrid Atlas Building with Deep Registration Priors
Registration-based atlas building often poses computational challenges in high-dimensional image spaces.
MS$^2$-Transformer: An End-to-End Model for MS/MS-assisted Molecule Identification
Manually interpreting the MS/MS spectrum into the molecules (i. e., the simplified molecular-input line-entry system, SMILES) is often costly and cumbersome, mainly due to the synthesis and labeling of isotopes and the requirement of expert knowledge.
