Building and Applying an Ontology-Based Medical Graph Database
This project took place in summer term 2021, you CAN NOT apply to this project anymore!
Results of this project are explained in detail in the final documentation .
- Sponsored by: Smart Reporting
- DI Incubator: Startup Smart Reporting
- Project Lead: Dr. Ricardo Acevedo Cabra
- Scientific Lead: Dr. Michael Strobel and Su Hwan Kim
- TUM Co-Mentor: PhD candidate Philippe Sünnen and PhD candidate Özge Sahin
- Term: Summer semester 2021
Smart Reporting is one of the world’s top startups in digital health. Our mission is to enable AI assisted diagnostics for the benefit of doctors and patients around the world. Already today, our award-winning software is used by thousands of doctors and institutions, including some of the world’s leading experts in radiology.
Contribute to something that makes a difference! What is the project about?
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Research on the application of medical ontology-based graph databases for structured clinical documentation and decision support
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Design, development and implementation of a proof of concept for an incrementally growing medical graph database
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Research on the dynamic visualization of medical graph databases
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For the purpose of the project, publicly available medical ontologies (e.g. RadLex) as well
as Smart Reporting ́s structured medical reporting template database will be used
Who are we looking for?
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You have advanced knowledge of graph algorithms, graph database know-how is a plus
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You eager to expand your existing knowledge of modern data science methods (supervised / unsupervised learning, dimension reduction, SVM, ensemble learning and
neural networks / deep learning)
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You have experience in programming (we use JavaScript / TypeScript and React for
visualization and Python (Scikit-Learn and TensorFlow) for data science, knowledge of
those is a big plus)
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You love to solve problems, think outside the box and learn new things
What do we offer?
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The opportunity to drive a cutting-edge research project on graph database-based medical knowledge mapping
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A high-profile, international team of medical doctors, software engineers and data scientists
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Profit from our network in healthcare
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The chance to work in a leading digital health startup that enjoys rapid growth and
significant funding from top-tier investors and EU grants
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Work on a meaningful project that improves healthcare and people’s lives
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A beautiful office in the heart of Munich, Odeonsplatz and Friedensengel
Could you see yourself in this project? Then we’re happy to hear from you!
Accepted students to this project should attend (unless they have proven knowledge) online workshops at the LRZ from 06.04.2021 - 09.04.2021 (9:00 AM to 5:00 PM). More information will be provided to students accepted to this project.