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Analysis of patient records

Use Case

Analysis of patient records

Electronic patient records can be evaluated using machine learning algorithms. This automatically provides doctors with suggestions for diagnoses and therapy options.



In the health sector, patient records are increasingly standardized (electronic patient records), so that they can be evaluated and are uniformly available for patients, doctors and health insurance companies.



Patient records can be evaluated using Machine Learning algorithms and patterns such as symptoms of diseases and side effects of drugs can be identified at an early stage.



Doctors automatically receive suggestions for diagnoses or therapy options and can use their personal impression to specify this information and determine the diagnosis or therapy.

More Use Cases

Handwritten documents can be read out and prefilled using machine learning algorithms. By further input, these documents can be edited again, which again benefits the accuracy of the algorithm.

Diagnostic suggestions can be made by analyzing X-ray or MRI images using an algorithm.

Through standardized images of different leathers, a machine learning algorithm can classify leather and assign it to the right garments.

Photos of defective spare parts are analyzed by a machine learning algorithm and the damage is classified. This information is used in the development of new products and in the selection of suppliers.

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