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We are Praxa Sense, a young medtech start-up working on the development of an innovative, data-driven device that enables patients to monitor their vital signs at home. We enable data collection over the long term, helping the general practitioner to diagnose diseases earlier. Our goal is to improve the medical processes by making products that perfectly combine hardware, software, and user experience. At this moment we are on the lookout for someone who can take care of the user experience-side of the product. A challenging and responsible vacancy with a lot of freedom and learning possibilities!
We are looking for a computer science student who is interested in an opportunity to improve and further develop a machine learning algorithm to detect the most common heart rhythm disease called Atrial Fibrillation (AF) and to expand the model for other heart rhythm diseases. The existing model is based on Convolutional Neural Network (CNN) technique. Public datasets of arrhythmia patients have been used to train and test the model. Your challenge will be to optimize the data preparation such as noise detection and correction and ECG-lead conversion to improve the model in detecting AF. Also, you can think along in developing the model further for other arrhythmias.
AF is the most common cardiac arrhythmia, affecting around 3% of adults and 10% of those aged above 75 years. Heart rhythm diseases are hard to recognize due to the nature of the symptoms. Current tools used in the medical field are not optimal for early diagnosis because of the short measuring times and inefficient algorithms. We will bridge this gap by enabling early diagnosis with a user-friendly long-term monitoring device that automatically analyses the data using top-class algorithms. By detecting heart rhythm diseases early, serious consequences, like strokes, can be prevented.
Interested and want to know more? Send an e-mail to hr@praxasense.com
Ambitious, young and fun healthcare startup creating the future of home monitoring. Join us on our mission to create high-class technical solutions to the pressing problems of the healthcare system in a durable way.
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