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Found 5 papers, 1 papers with code
Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks
Experiments on four interaction datasets show that our proposed method achieves accurate and calibrated predictions.
GNE: a deep learning framework for gene network inference by aggregating biological information
However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions.
Ranked #1 on
Gene Interaction Prediction
on BioGRID(yeast)
(using extra training data)
Image Understanding from Experts' Eyes by Modeling Perceptual Skill of Diagnostic Reasoning Processes
Eliciting and representing experts' remarkable perceptual capability of locating, identifying and categorizing objects in images specific to their domains of expertise will benefit image understanding in terms of transferring human domain knowledge and perceptual expertise into image-based computational procedures.
