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

Management decision support.Webiomed.Analytics

Predictive analytics built on the basis of clinical practice data (RWD) from electronic health records (EMRs) and AI-generated digital patient profiles.

It helps managers to make prompt decisions based on data analysis

Webiomed.NLP

Extraction of features from unstructured medical records

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

Webiomed.DataSet

 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.

 

RWE/RWD

Collection, analysis and use of health data and health care processes obtained from identified electronic health records (Real World Data, RWD).

Research projects

Participation in scientific research and development in the field of artificial intelligence, incl. in grants, publications and participation in conferences.