AI for Pathologists. Deeper Insights, Unwavering Confidence.
Whole slide imaging meets explainable AI. Backed by peer-reviewed research and academic partnerships.
For Research Use Only.
Why It Matters
Integration
Explainability
Explainability
Built for multi-modal research. Pathology slides today; clinical and genomic data in development.
Explainability
Explainability
Explainability
Transparent overlays show how patterns are highlighted, supporting interpretability and explainable AI in pathology research. Researchers can review, refine, and publish with clarity.
Efficiency
Explainability
Efficiency
Supports research workflows without disruption, helping teams handle larger study cohorts more effectively.
What Pathologists Get
Case triage engine: Supports prioritization of high-volume cases in research studies.
ROI highlighting with confidence scoring: Flags regions of interest and assigns scores for reproducibility.
Exportable overlays and metrics: Ready for publications and collaborations.
Integrated feedback loop: Researcher input continuously refines results, improving usability over time.
Planned features: Voice navigation and genetic overlays to expand interactivity and multimodal capabilities.
HOW IT WORKS
Simple. Intuitive. Secure for research workflows.
Upload: Drag and drop WSI slides into the secure platform.
Process: AI analyzes image structures; internal benchmarks show processing in under 10 minutes per slide.
Review: Transparent overlays display directly on the slide.
Report: Export results to CSV or PDF. LIS/PACS compatibility studies in development.
Grounded in Research. Built by Experts.
Peer-Reviewed Research
Studies span prostate, breast, gastric, kidney, and lung cancers. Explore methods, datasets, and results used in SAINT research. Peer-reviewed publications demonstrate progress in digital pathology AI. Early internal results indicate exploratory comparison with expert reviews.
Academic Partnerships
Backed by Northeastern, the Roux Institute, and the Amal Lab, with peer-reviewed studies across multiple cancers. SAINT is built by AI scientists, clinical collaborators, and pathology advisors to support reproducible research.
Built by Experts
Led by Professor Saeed Amal with a team of AI researchers, pathology experts, and academic collaborators, advancing explainable AI and reproducible digital pathology research.