AI-enabled predictive analytics and risk assessment in healthcare

Reliable digital physician assistant to identify high-risk patients

Clinical decision support system Webiomed.DHRA

Comprehensive assessment of de-identified medical data in order to identify risk factors, forecast the development of diseases and identify suspicions of missed diagnoses


Extraction of features from unstructured medical records

Such features include symptoms, blood pressure data, patients height and weight, unstructured objective data, lab tests from case reports and much more.


 Accumulation of de-identified data from medical records, feature extraction and dataset creation for machine learning and research

Machine learning models

We provide direct API access to our predictive analytics models.

We create various models based on machine learning for our system. 

The main ones are predictive analytics models, which allows the system to forecast possible events with the patient's health. However, we also need models for extracting features from text records and models for identifying suspected diseases.