Case Studies

Learn how leading AI teams across healthcare build datasets and models. Explore success stories and real-life use cases.

We work with organizations at the forefront of AI.
Memorial Sloan Kettering Cancer Center
Brigham and Women's Hospital
Massachussetts General Hospital
How Paige gets high quality training and evaluation data to enhance breast cancer detection AI
How Eko Health develops AI to identify abnormal lung sounds
search engine
How Consensus evaluates and trains their scientific search algorithm

5 case studies show how leading AI teams achieve expert-quality data annotation at scale

Download Case Studies ā†’
How Aiberry builds explainable mental health AI with a novel affect video dataset
How Volastra Therapeutics quantifies chromosome instability at scale with AI
medical device
Accelerating AI for GI with accurately annotated colonoscopy video
Medical device
How Centaur Labs helped VUNO accelerate FDA clearance for its brain MRI segmentation model
Centaur's mobile-first labeling tools enable us to quickly and conveniently gather results from our residents. We've accelerated our research by building and refining our ML models on COVID-19 pathologies in near real time. Centaur Labs has been a crucial partner throughout.
Andrew J. Goldsmith, MD, MBA
Director of Emergency Ultrasound, Emergency Medicine
Brigham & Women's Hospital
Segmenting graft-versus-host skin disease is a complex and time consuming task. Centaur collected over 10 vetted opinions per image from their network, and combining those segmentations together produced amazingly high-quality annotations.
Dr. Eric Tkaczyk
Director, Vanderbilt Dermatology Translational Research Clinic
We knew we couldnā€™t rely on individual neuroradiologistsā€”or traditional, non-medical outsourced labeling servicesā€”to segment different kinds of hemorrhages in thousands of brain CT scans. Centaur tackled this problem quickly and accurately, enabling us to focus our time on building cutting-edge AI.
Raahil Sha
CTO, Zeta Surgical
Any data scientist will love working with Centaur Labs. They provided us with rich information on labeler disagreement that is both critical to publishing results of our work and unlike any labeling vendor out there. Our project also had unique requirements for the population of labelers, and Centaur was able to recruit over 650 labelers that met those requirements.
Michael Bell, PhD
Senior Data Scientist, Mercury Data Science

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