The startup utilizes natural language processing and machine learning to analyze healthcare data, enhancing the accuracy of clinical decision-making and operational workflows. By improving data interpretation, it enables healthcare providers to make more informed decisions and optimize resource allocation.
Funding
$2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Healthcare data is often unstructured and complex, making it difficult to extract meaningful insights for clinical decision-making and operational efficiency. The lack of standardized data formats and the presence of free-text clinical notes hinder the ability to leverage data for analytics and predictive modeling.
Solution
Lexigram offers a data API that structures unstructured healthcare data, enabling users to extract clinical concepts and relationships. The platform utilizes natural language processing (NLP) and a proprietary medical knowledge graph to identify entities such as drugs, diseases, and symptoms within patient records. By structuring this information, Lexigram facilitates improved data analytics, predictive modeling, and integration with electronic health record (EHR) systems. The API allows for the extraction of targeted information while preserving contextual data, addressing the challenges of data quality and ontology selection.
Target Audience
Lexigram's primary customers are healthcare providers, technology vendors, and healthcare analytics companies seeking to leverage unstructured data for improved clinical decision-making, research, and operational efficiency.
Features
- Clinical concept extraction from unstructured text using NLP
- Proprietary medical knowledge graph that surfaces clinical entities and their relationships
- Identification of codes from ICD, HCPCS, and LOINC associated with clinical concepts
- Aggregation of drug information from RxNorm, DrugBank, FDA Orange Book, National Drug Code, and ATC
- Real-time chat application integration for condition and anatomy identification
- API access for integration with EHR systems and other healthcare applications
- Predictive analytics capabilities for predicting patient outcomes