Meta-analysis of 28 FFS studies shows experimental design choices explain 33% of variance in new method performance against baselines.
In silico clin- ical trials: concepts and early adoptions
5 Pith papers cite this work. Polarity classification is still indexing.
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PepMorph generates morphology-targeted peptides via a Transformer conditional VAE and reports 83% success under CG-MD validation.
A coupled patient-device respiratory model integrating lung mechanics, gas exchange, and respiratory control is validated as fit-for-purpose for preclinical in silico trials of automated weaning under ASME V&V 40 and FDA guidelines.
TriMod-DTI uses contrastive learning across 1D sequences, 2D graphs, and 3D structures to outperform prior DTI methods on three benchmarks.
citing papers explorer
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Bias in Filter Feature Selection Evaluation: A Meta-Analysis of Datasets, Baselines, and Experimental Design Choices
Meta-analysis of 28 FFS studies shows experimental design choices explain 33% of variance in new method performance against baselines.
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Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
PepMorph generates morphology-targeted peptides via a Transformer conditional VAE and reports 83% success under CG-MD validation.
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Validation of a Computational Respiratory System Model for Mechanical Ventilation
A coupled patient-device respiratory model integrating lung mechanics, gas exchange, and respiratory control is validated as fit-for-purpose for preclinical in silico trials of automated weaning under ASME V&V 40 and FDA guidelines.
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A Triple-Modal Contrastive Learning Framework with Sequence, Graph, and 3D Features for Drug-Target Interaction Prediction
TriMod-DTI uses contrastive learning across 1D sequences, 2D graphs, and 3D structures to outperform prior DTI methods on three benchmarks.
- TRAPS: Treatment-Assignment Prediction via Pathway-informed Stratification