All Competitors

Brain MRI foundation model pretrained with masked image modeling on roughly 57,000 multi-contrast head scans for brain tumor diagnosis.

Generative image perturbation autoencoder predicting cellular morphological responses to chemical and genetic perturbations from control images.

Health acoustics foundation model that turns short clips of coughs and breaths into embeddings for building acoustic biomarker models with less data.

Chromosome-wise explainable autoencoder that compresses DNA methylation array data up to 400-fold while keeping CpG groupings interpretable.

Explainable autoencoder for transcriptome analysis that uses SHAP attribution on latent variables to identify critical genes driving gene expression.

Self-supervised medical vision-and-language pretraining via multi-modal masked autoencoders that reconstruct masked image patches and text tokens.

Single-cell perturbation prediction model that forecasts transcriptional responses to drug combinations and doses never experimentally measured.