Solutions

Experts to annotate
audio at scale

Audio clips from medical devices are critical indicators of patient health, and can be leveraged to train predictive algorithms that detect heart conditions, lung abnormalities, and more.

Our annotation platform is tailored specifically to medical audio clips, with features such as range selection, spectrogram integration, and motion data integration.

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Use cases

Heart auscultation

Tag the presence of, intensity and time range of heart murmurs, rubs, clicks, S1, S2 and more.

Lung auscultation

Tag the presence of, intensity and time range of crackles, ronchi, wheezes, stridor, breath sounds and more.

Artery auscultation

Tag the presence of, intensity and time range of bruits and Korotkoff sounds.

Abdominal auscultation

Tag the presence of, intensity and time range of bowel sounds, rubs, or vascular bruits.

Clinical session recording

Tag intonation, emotion, symptoms and medications discussed in clinical interactions.

Annotation types

Classification

Range selection

Eko Health

Eko Health uses Centaur Labs to annotate lung sounds for its AI-enabled digital stethoscope that detects heart and lung abnormalities.

20,000

Lung sound recordings

120,000

Expert opinions

Week turnaround

.87 to .92

AUC

Testimonials

Trusted by AI leaders across healthcare

“The Centaur Labs platform provided labels at a scale that was 10x, or 20x, anything we had done by ourselves. Tremendous scale, tremendous throughput, and high quality labels.”

Daniel Barbosa

Machine Learning Engineer at Eko

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"I was very impressed by the Centaur Labs approach to annotation. They provided us with excellent labels on what was a difficult task and noisy data. Centaur Labs understood what the issues were from the beginning, and were able to help steer the project for us."