Extract entities from public health data

This model is specialized in health-related text analysis in colloquial language within the domain of Public Health. It is designed to identify and extract various entities such as access to care, employment and financial Status, various social factors, substance abuse, health status, etc., informally presented in public data.

Use the provided Streamlit playground application to test this service.

- Extracted Entities: Access_To_Care, Community_Safety, Overweight, Pregnancy, Environmental_Condition, Employment, Financial_Status, Food_Insecurity, Geographic_Entity, Healthcare_Institution, Obesity ,Race_Ethnicity, Population_Group, Insurance_Status, Legal_Issues, Mental_Health, Smoking, Quality_Of_Life, Social_Exclusion, Social_Support, Spiritual_Beliefs, Substance, Violence_Or_Abuse, Education, Housing, Alcohol, Disease_Syndrome_Disorder, Diet,Relationship_Status, Drug, Alcohol, Psychological_Condition, Employment, Disease_Syndrome_Disorder, Substance, Substance_Quantity and more
- Assertion Status Labels: Hypothetical_Or_Absent, Present_Or_Past, SomeoneElse
- Relation Extraction Labels: Disease_Syndrome_Disorder-Drug, Drug-Disease_Syndrome_Disorder, Drug-Mental_Healt,Mental_Health-Drug, Allergen-Drug, Drug-Allergen, Psychological_Condition-Drug, Drug-Psychological_Condition, BMI-Obesity, Obesity-BMI , Alcohol-Substance_Quantity, Substance_Quantity-Alcohol, Smoking-Substance_Quantity, Substance_Quantity-Smoking, Substance-Substance_Quantity, Substance_Quantity-Substance