Robust NLP Labeling for Healthcare

Use cases

Customizable, advanced NLP Labeling to drive innovation for Healthcare organizations

Improve patient care

Easily transcribe and label patient-physician appointment notes, freeing up doctors’ time to focus on what they do best.

Streamline EHR/Clinical documentation

Leverage quality NLP models to organize electronic health records and categorize patient information.

Quality clinical decision support

Build high-performance clinical decision support (CDS) tools fed on quality, labeled data.

Benefits

Realize the Benefits of NLP for Healthcare

The most robust tool for healthcare NLP labeling

If you’re extracting information or training a model to transcribe and categorize patient encounters, you need a robust, configurable NLP labeling tool.

Hierarchical labeling
Configurable UI
PII anonymization
Audio transcription

Label efficiently, quickly, and accurately

Manually labeling medical data, sifting through raw transcriptions, and trawling through granular medical labels can drain time. Time that could be spent building quality models.

ML-assisted labeling
Hotkeys and clickless labeling
Label searching for large taxonomies
Entity linking

Automate monotony away

Creating custom QA reports, reviewing project progress, and manually trying to get the insight can get monotonous and slow production time. It doesn’t have to.

Automated imports and exports
Automated project creation
Quickly surface inter-annotator disagreements
Automated reporting

Why Datasaur?

Evolve and deliver business impact with deep NLP expertise

Robust audio labeling tools

Transcribe doctor-patient interactions and label efficiently. Features include: speaker diarization, transcription editing, multi-language support, etc.

Easy of use

With Datasaur, you can handle layered and complex medical labeling easily and efficiently. Label data quickly and accurately, even with a huge taxonomy.

Genuine support for labeling needs

Save time and frustration. Get a PM who understands the intricacies of your labeling workflow & takes time to understand each request.

As seen on

We [Consensus] had a very complex and specific set of annotation needs. Datasaur was able to address those needs efficiently and effectively.

Eric Olson, Co-founder and CEO, Consensus

Information labeling tasks has been reduced by 80% which has allowed us to optimize our workflow much more, allowing us to focus on other areas that are also priorities for us.

Product Manager, LegalTech

"We looked at Prodigy, LightTag, LabelBox, Scale and more. You really can't beat Datasaur for their suite of features and price point."

Director of Data Science, Financial Institution

The most advanced NLP labeling tool for

Healthcare Organizations