Diagnostic delays averaged six months in low-resource areas. AI now analyzes tissue and drafts reports to accelerate care.
A computational pathology laboratory at Harvard Medical School and Mass General Brigham analyzes tens of millions of high-resolution disease images to advance diagnostic precision.
Pathology images are massive and complex, making it difficult to identify specific disease markers without extensive manual annotation. In...
“Our particular focus has been on digital and computational pathology because it’s a sort of modality that has recently started to be digitized. There’s large amounts of data that is collected. It’s a challenging and interesting problem because the images are very large and we don’t typically know what we’re going to find.”
Computational pathology research lab developing AI for cancer diagnosis.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
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Immunologists hand-labeled individual cells, stalling discovery. GenAI now automates annotation, cutting research timelines by 50%.
Predicting a single protein binding took 2,000 hours. Deep learning models now complete the task in just 15 minutes.
Silos forced teams to manually chase data. Now, AI agents identify adverse events in seconds, eliminating weeks of cross-referencing.
Attorneys juggled fragmented tools to search 50,000 cases. An AI orchestrator now routes queries to sub-agents in a single chat.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.