Research Prototype

Computational Biology.
Accelerated.

Advanced Pathology Workstation integrating high-resolution Whole Slide Imaging (WSI) with multimodal AI.

1. Diagnosis
Cancer Subtype Prediction straight from histopathological gigapixel images using vision transformer backbones.
2. Prognosis
Mutational Biomarker Identification paired with proprietary Graph Attention Autoencoders for advanced patient risk stratification.

The Core Challenge

Whole Slide Images (WSI) are massive—often exceeding 100,000 x 100,000 pixels. Traditional Convolutional Neural Networks (CNNs) struggle to process this context globally without destroying clinical latency.

OncoGemma addresses this by extracting meaningful 256x256 tissue patches, filtering background noise, and creating a spatial graph.

"We treat the tissue not as a picture, but as a complex biological network of interacting cellular neighborhoods."