Solutions
From AI innovation in emergency medicine to cardiology, Centaur Labs provides researchers on the cutting edge of their fields with high-quality medical data annotations at unprecedented speed and scale.
Advancing medical and biomedical research with cutting edge data annotation capabilities.
Researchers are exploring ways to improve clinical decision making, whether through improved skill assessment and development, or through AI-enabled tools proven to enhance performance.
Medical education
AI-enabled clinical decision support
Increasingly AI developers and researchers are partnering to develop AI and ML algorithms that can advance the medical and life sciences.
Training datasets
Test and validation datasets
Dataset insights
Researchers across medical and biological disciplines are leveraging large and diverse datasets for analysis and discovery.
Normalizing ‘dirty’ data
Annotating features within datasets
Access millions of annotations weekly from a network of thousands of medical experts, taking models from exploratory analysis to deployment in weeks, not months.
Experience how label quality is built into the Centaur Labs system, with frequent performance measurement and pay-for-performance incentives.
Leverage more reliable statistical information to inform your algorithm training plan.
Worry less with leading privacy and security capabilities.
Lean on Centaur Labs’ expertise as the only annotation company focused on health, biological and scientific data.
From pathology slides to surgical video to unstructured clinical notes, get all of your annotation needs in one single platform.
Researchers at the Massachusetts General Brigham Neurology Department.
Test if trained neurologists could accurately identify 6 common EEG findings within an expert-annotated dataset of EEGs, and if they could improve over a short time.
Neurologists attending the annual three-day Critical Care EEG Monitoring Research Consortium Conference downloaded the DiagnosUs mobile application and shared their opinions on the EEGs. The app offered instructions and feedback as neurologists shared answers.
The results revealed that experts’ accuracy at identifying EEG findings improved with more exposure—in some classes, by over 150%.
Across three labeling tasks including malignancy classification and lesion recognition, Centaur collected over half a million opinions from its network of experts. Recent research published in the Lancet assessed how accurate board-certified experts with 10+ years experience were at this multi-class skin-lesion labeling task. The performance of the Centaur’s network without any experience exclusion criteria was more accurate (78.1%, p<0.001, vs 74.7%) than those physicians.
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