Healthcare and Genomics
Genomic data, clinical records, and medical imaging share structural properties that make them candidates for QTT compression. Structural representation could enable real-time querying across datasets that currently require distributed clusters.
High-dimensional healthcare data at scale
Genomic Sequencing Data
Massive, high-dimensional, structurally regular. Genomic data is fundamentally structured: sequences have local correlation, variant patterns are spatially organized, coverage is uneven. These structures make QTT compression effective.
Clinical Data Integration
Multiple access patterns over the same patient records. One unified structural representation serves clinical queries, research analytics, and compliance auditing without format conversion.
Medical Imaging Compression
Exploiting spatial structure in volumetric imaging. MRI, CT, and genomic visualization all benefit from compression that preserves spatial relationships.
Exploratory. Structural classification in progress.
This domain represents a research direction. For the current shipping product and proven economics, see HX-SDP.