Build innovative digital health applications with Priberam’s cognitive platform that extracts valuable information from different types of unstructured health data to facilitate the discovery of key information hidden in clinical records.

Health records analysis

Automatically extracted family history, symptoms, diseases, clinical procedures, medications, allergies and lab results from electronic health records can provide valuable data and insights to clinical practice. The data and insights can also be used to predict complex drug interactions in individual patients.

Predict complex drug interactions in individual patients

Unique insights to help improve the lives of a patient group

Discovering hidden information

Putting together and relating information extracted from clinical diaries, reports from diagnostic imaging procedures, lab results, discharge notes, etc. provides unique insights that can be delivered to the care team or help improve the lives of a patient group.

Visualization

Innovative visualizations can bring sense into the avalanche of data extracted from electronic health records. A patient timeline together with highlights for the most important allergies, history, chronic diseases or a graph depicting the links between patients in a clinical trial helps solving today’s health challenges.

Helping to solve today’s health challenges

Advanced information retrieval platform for health data

The information that can be extracted from millions of health records can help researchers profile patient groups or develop new treatments. Priberam’s text analytics and cognitive search engines provide an advanced information retrieval platform for health data.

Digital Patient

This project will take advantage of the massive analysis of non-structured information that currently is not processed to improve the diagnosis and treatment of the patients.

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