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Leiden University Medical Center (LUMC) is a modern university medical center for research, education and patient care with a high quality profile and a strong scientific orientation.

Its unique research practice, ranging from pure fundamental medical research to applied clinical research, places LUMC among the world's top training and research hospitals. This enables them to offer patient care and education that is in line with the latest international insights and standards – and helps to improve medicine and healthcare both internally and externally.


Administrative tasks are an essential but time consuming part of healthcare. Doctors have to register everything they discover within a patient’s file. Symptoms, diagnosis, medication and treatment plans all have to be noted. This is time which could be better spent with patients.


Together with LUMC, we’re dramatically reducing the administrative workload. To achieve this, we developed a fit-for-purpose application that records, transcribes and analyses doctor - patient interviews automatically.

Unlike other speech recognition solutions, this application does more than just transcribing the information. The tool recognises medical terms and presents physicians with an analysis that responds to each of the questions they asked during the interview: how long has the patient been unwell, are the symptoms worse at certain times than others, and so on. Specialists can then review the information and transfer it to the right spot in the EMR-system with the click of a button, allowing doctors to use their valuable time providing patient care.

Normally, doctors would enter the data manually, using their own words and structure, making data analysis almost impossible. With this technology in place, all data is saved within the patient file without doctor intervention, following a consistent structure for every department and patient. This accelerates the process for physicians and simplifies collaboration between medical departments. Additionally, the automation enables data analytics on symptoms and treatments at a later stage.

The focus of this initial project was to reduce the administrative load, followed by more advanced data analysis. Machine Learning is better at recognising patterns than humans will ever be. By comparing complaints, diagnoses and other patterns, it is likely that a diagnosis can be set in an earlier stage.

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