Machine Learning in pulmonary function diagnostic
What’s it about?
Due to the current COVID-19 pandemic, people’s state of health is moving more and more into the focus of society.
As COVID-19 is a respiratory disease, patients suffering from chronic obstructive pulmonary disease, colloquially known as smoker’s cough, are classified as at-risk patients. Unfortunately, early detection of the disease in its early stages is only possible to a limited extent even for experts in the context of normal routine preventive examinations with a reliable measurement of the pulmonary function values, as the measurement is highly dependent on the procedure and the patient.
In the context of a project of FHWS in cooperation with the University of Greifswald and Lothar Medtec GmbH as well as Empolis Information Management GmbH, it was investigated to what extent a machine learning model can support the diagnosis of the early stage of COPD. A special requirement here was the interpretability of the model for the treating physicians. Thanks to the cooperation, the students had access to extensive anonymised data from the SHIP study.
Simon Heilig, Matthias Keckl, Niels Knoll, Joshua Meder, in their 6th semester of the bachelor’s in Computer Science during the scheduled Research Project.
Supervised by: Prof. Dr. Steffen Heinzl, Prof. Dr. Frank-Michael Schleif