Public Health - Biomedical NLP Demos & Notebooks

This demo extracts and classifies healthcare-related terms from the documents transferred from the patient’s own sentences. (...)

This demo extracts healthcare-related terms from the documents transferred from the patient’s own sentences. (...)

Assertion status model used to predict if an NER chunk refers to a positive finding from the patient (Present_Or_Past), or if it refers to a family member or another person (SomeoneElse) or if it is mentioned but not as something present (Hypothetical_Or_Absent). (...)

This demo showcases a classification model designed to detect mentions of side effects in patient-written texts. (...)

These models classify self-report the exact age into social media data. (...)

These models classify self-report the exact age into social media data. (...)

This model extracts disease entities in Spanish tweets. (...)

This model classifies people non-adherent to their treatments and drugs on social media. (...)

This model classify public health mentions in social media text. (...)

The PHS-BERT Respiratory Disease Classifier Model is a specialized text classification system, engineered to accurately identify and categorize textual mentions of four prominent respiratory diseases: Asthma, Chronic Obstructive Pulmonary Disease (COPD), Emphysema, and Chronic bronchitis. (...)

The PHS-BERT Heart Disease Classifier Model is a specialized text classification system, engineered to accurately identify and categorize textual mentions of three prominent cardiovascular diseases: Hypertension, Coronary Artery Disease, and Myocardial Infarction. (...)