RosettaCore

The AI backbone powering healthcare clarity and computability.

How HER-BERT Understands Clinical Language

At the core of HER-BERT is a physician trained NLP engine that understands more than just words — it understands clinical meaning. It works in three precise steps.

  1. Named Entity Recognition - Finds key terms in clinical narratives.

  2. Semantic Interoperability Engine - Maps those terms to standard codes like ICD and SNOMED.

  3. Co-referenced Resolution - Understands context (like who “ the patient’ is)

This pipeline transforms free text into structured, actionable intelligence — quickly and reliably.

Two Outputs, One Engine: RosettaMD & RosettaCore

From a single line of clinical text, HER-BERT delivers two powerful interpretations: RosettaMD offers clear, human_readable definitions for patients and families . RosettaCore delivers structured, machine readable data for healthcare systems.

Together they ensure clarity for individuals and computability for institutions — unlocking the full potential of every medical narrative.

Structured Intelligence for Health Systems

Flowchart explaining unstructured healthcare narrative processing using NLP engine powered by AI, specifically HER-BERT. It shows a patient's prescription of 20 mg lisinopril daily feeding into the NLP engine, which generates data for RosettaMD, for medication details, and RosettaCore, for data normalization.

RosettaCore transforms clinical narratives into standardized, machine-readable data.
The image here shows how one stream of text can become structured outputs for:

  • Medical coding

  • NLP tagging

  • Patient similarity

  • Cohort building

  • And more

All mapped to industry standards like SNOMED, ICD, and CPT.

This is where HER-BERT becomes healthcare’s most versatile AI engine—quietly powering systems behind the scenes.

HER-BERT in Action: End-to-End Semantic Transformation

From ambiguous input to precision output—this is HER-BERT’s full pipeline at work.
Whether it’s a clinical narrative, search query, or continuity of care document, HER-BERT applies deep semantic processing to extract, normalize, and map medical concepts across terminologies.

From the same patient note, it delivers accurate codes, NLP tags, cohort segmentation, FHIR resource mappings, and more—all in milliseconds.

This is how data moves in modern healthcare—with HER-BERT behind the wheel.

HER-BERT Outperforms Across the Board

HER-BERT isn’t just faster — it’s smarter.
Validated on the HERB benchmark, HER-BERT leads in both top-1 and top-5 accuracy, outperforming BioBERT, UAE-BERT, GPT-4, and GPT-3.5.

With lightning-fast 150ms response times and 20x the speed of GPT-4, it sets a new standard in medical NLP for real-time, clinical-grade performance.

This is precision at scale—engineered for deployment. it is, the way you tell your story online can make all the difference.

Comparison chart showing HERB benchmark performance with metrics like response time, accuracy, and speed. Top-1 accuracy reaches 150ms response time, 20 times faster than GPT-4, with the highest top-1 match accuracy among tested models: GPT-3.5, GPT-4, BioBERT, and UAE-BERT. The chart includes a line graph illustrating accuracy percentages for these models.