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Data Science in Medicine

Health data analytics is one of the main drivers for the future of medicine. Various sources of big data, including patient records, diagnostic images, genomic data, wearable sensors, are being generated in our everyday life by health care practitioners, researchers, and patients themselves. Data science aims to identify patterns, discovering the underlying cause of diseases and well being by analyzing this data.

Medical data science is an interdisciplinary domain, which brings together informatics, health care, and clinical science experts to solve real-world problems. In this seminar, you will explore different phases of data science in medicine, including challenges of integrating multiple types of data, data quality and sources of data, applications of descriptive and machine learning algorithms in medicine, federated learning, and evaluation and validation methods. Seminar topics will focus on data management and analytics methods and their specific applications in medicine.

If you have any question, please do not hesitate to send a message to mou@dbis.rwth-aachen.de.

Max. number of participants: 8

 

 

 

Prerequisites

Recommended Preknowledge: Basics of databases and/or (web-based) information systems.

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