Google Healthcare Natural Language API

A Google Healthcare Natural Language API is a Healthcare natural language API that is a Google Cloud Healthcare API.

• Context:
  • It can be used to extract medical information from clinical text items in a structured form that's suitable for analysis.
  • It can interpret clinical terminologies, symptoms, diagnoses, treatments, and other health-related data from clinical text.
  • It can support clinical data standards and terminologies like SNOMED CT, LOINC, ICD-10, and others.
  • It can be used by healthcare organizations, clinical researchers, and healthcare software developers for tasks such as creating medical records, clinical research, data analysis, and building healthcare applications.
  • It can use techniques from Natural Language Processing (NLP) and Machine Learning to understand and extract information from clinical text.
  • It can offer capabilities like entity extraction, concept mapping, semantic annotation, negation detection, and relation extraction from clinical text.
  • It can provide services to map the extracted entities to medical codes.
  • It can provide a syntactic analysis of the text.
  • It can be used to:
    • extract medical information from a Doctor's Note and map it to ICD-10 codes.
    • understand and categorize symptoms described in a patient's clinical note.
  • …
• Example(s):
  • …
• Counter-Example(s):
  • Microsoft Text Analytics for Health.
  • …
• See: Google Cloud Healthcare API, Clinical Text Item, Natural Language Processing, Clinical Decision Support System, Clinical Data Standard.

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References

2023

• https://cloud.google.com/healthcare-api/docs/how-tos/nlp
  • QUOTE: The Healthcare Natural Language API provides machine learning solutions for deriving insights from medical text. The Healthcare Natural Language API is part of the Cloud Healthcare API. ...
  • The Healthcare Natural Language API parses unstructured medical text such as medical records or insurance claims. It then generates a structured data representation of the medical knowledge entities stored in these data sources for downstream analysis and automation. For example, you can:
    • Extract information about medical concepts like diseases, medications, medical devices, procedures, and their clinically relevant attributes
    • Map medical concepts to standard medical vocabularies such as RxNorm, ICD-10, MeSH, and SNOMED CT (US users only)
    • Derive medical insights from text and integrate them with data analytics products in Google Cloud

2020

• 2020-11 https://cloud.google.com/blog/topics/healthcare-life-sciences/now-in-preview-healthcare-natural-language-api-and-automl-entity-extraction-for-healthcare
  • QUOTE: ... Today, we are excited to launch in public preview a suite of fully-managed AI tools designed to help with these challenges: Healthcare Natural Language API and AutoML Entity Extraction for Healthcare. These tools assist healthcare professionals with the review and analysis of medical documents in a repeatable, scalable way. We hope this technology will help reduce workforce burnout and increase healthcare productivity, both in the back-office and in clinical practice. ...
  • To facilitate analysis of medical insights at scale, the Healthcare Natural Language API automatically normalizes medical information against an industry-standard knowledge graph such as Medical Subject Headings (MeSH) or International Classification of Diseases (ICD). ...

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