Diagnostic Support Tool

Healthcare • Artificial Intelligence • Digital Experience


Emergency Medical Systems (EMR) hold thousands of records including patient histories, physical exams, examination results and diagnostics.

However, this data is difficult to access and is highly unstructured, making it tricky to analyze and use for decision making.

Patient diagnosis is a complex process involving a lot of variables; having a diagnostic support tool can be useful for training and validation purposes.


Designed and built a model to predict and output a list of potential diagnoses based on a patient’s history, physical exams and other patient information.

Used NLP/NLU to extract and analyze text data to create relevant features for the model.

Live integration of the diagnostic tool with the EMR so that it is always working with the most updated patient information.


Improved and standardized the diagnostic process with a decision- support tool.

Streamlined training of new clinicians.

Collected and pre-processed a massive amount of data for future analysis.