Collaborated with leading researchers to assess biomedical LLMs, advancing AI’s ability to answer medical queries and simplify complex scientific concepts.
A $750,000 grant from the Massachusetts Life Sciences Center will support Brigham & Women’s Hospital researchers in their efforts to transform medical research.
Know Centaur AI's new time range selection feature that speeds up medical video annotation, improving accuracy and efficiency in healthcare data processing.
Gamified data labeling enhances model accuracy from 70% to 93% in a case study with Eight Sleep, demonstrating the effectiveness of multimodal annotation.
Emphasized the importance of data curation practices in reducing bias in medical AI, promoting diverse datasets, expert collaboration, and fairness metrics for more equitable outcomes.
Partnered with SciBite to accelerate vocabulary curation, cutting the timeline by over two months through expert crowd-labeling, achieving 90.3–95.1% accuracy.
Collaborated with VUNO to annotate brain MRI data, contributing to FDA clearance for VUNO Med®-DeepBrain®, an AI tool designed to assist in early dementia detection.
CEO Erik Duhaime discussed AI safety in healthcare with AI Unleashed, addressing challenges in data, model oversight, and the future of human-AI collaboration.
Announcing a new DICOM labeling experience and text highlighting features, designed to improve medical image annotation and support better healthcare outcomes.
Centaur Labs completes SOC 2 Type II audit, reinforcing its commitment to data security, privacy, and operational excellence for customers and partners.
Worked with Volastra Therapeutics to annotate cancer cell images, supporting AI models in quantifying chromosomal instability and advancing cancer research.
Paige collaborates with Centaur Labs to enhance its algorithm, using high-quality data annotations to boost accuracy and performance in breast cancer detection models.
Centaur Labs contributes high-quality data annotations to enhance Consensus’ scientific search algorithm, improving accuracy and boosting research capabilities.
Learn how to automate your data pipeline with Centaur's end-to-end API integrations, streamlining workflows and enhancing efficiency for seamless data management.
RSNA 2022: Centaur Labs explores the importance of ensuring clinical AI safety at scale, offering insights on building trustworthy healthcare technologies.
Dandelion Health teams up with Centaur Labs to provide AI developers scalable access to high-quality clinical data, driving progress in healthcare technology.
The new AI-powered scientific search engine, Consensus, partners with Centaur Labs to generate high-quality, scalable scientific data labels for research.
From SMS to insurance claims, pathology reports, and scientific studies, this post explores the most common medical text datasets used for NLP in healthcare.
In the era of hybrid work, creativity and thoughtfulness are key to team success. Learn how we’re helping our team thrive, no matter where they work.
Learn about our partnership with Mayo Clinic spin out Lucem Health, and how clinical AI development teams can access high quality medical data annotations at scale.
Uncover the essence of Centaur Labs, a pioneer in combining human and machine intelligence for superior medical data labeling in the evolving healthcare landscape.
Learn more about how Centaur Labs is working with the Brigham and Women's Hospital team to develop multiple AI applications for point of care ultrasound.
Understand why traditional labeling pipelines are hard to scale—and discover how our solution can 10X your pipeline faster, with greater accuracy and efficiency.
Access dozens of open-source medical AI image datasets in formats like X-ray, CT, MRI, Ultrasound, Whole Slide Imaging, and more for research and training.
Examine the unique challenges of medical data labeling, why traditional methods fall short, and explore a more accurate, scalable alternative solution.
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