Hasso-Plattner-Institut
HPI Digital Health Center
  
 

Data Management for Digital Health

General Information

  • Open-for-all online educational course
  • Teaching staff: Florian Borchert, Orhan Konak, Dr.-Ing. Matthieu-P. Schapranow
  • Format: 4 Semesterwochenstunden (SWS) 6 ECTS (graded)
  • Location: Synchron web meeting during the time slots mentioned below. 
  • Schedule:
    • Tuesdays 11.00am (s.t.) CET
    • Thursdays 09.15am (s.t.) CET
  • First course:
    • Tuesday Nov 3, 2020 at 11.00am (s.t.) CET

Instructions to join the online lecture:

Please test the tool once before the first course in case you need to install a plugin or configure your local browser. Do not hesitate to contact anyone of us in advance, if you have any questions or encounter any issues when joining the seminar.

News

  • Thu Feb 11, 2021: In addition to the exercise III review, we scheduled a dedicated Q&A session for this slot, where you can discuss any open questions with us.
  • Tue Feb 02, 2021: Join our guest speakers Guest Speakers Prof. Dr. Alexander Meyer and Dipl.-Inf. Hauke Tönnies (announcement, slides H. Tönnies).
  • Thu Jan 28, 2020: Exercise III is online available in the student community.
  • Tue Jan 05, 2021: Join our guest speaker Prof. Dr. Reinhold Schäfer on his talk about "Personalized Oncology: Examples for Discussions in a Molecular Tumor Board." (announcement, slides).
  • Thu Dec 10, 2020: Exercise II is online available in the student community.
  • Tue Dec 08, 2020: Join our guest speaker Dr. Andreas Mock on his talk about "Data Science for Precision Oncology: Lessons Learned from the NCT/DKTK MASTER Program" (announcement, slides).
  • Thu Nov 19, 2020: Exercise I is online available in the student community.
  • Sam Oct 31, 2020: Connection details for the web meeting have been updated. Please check the updated instructions on this page.
  • Mon Oct 12, 2020: We are happy to announce that the upcoming course will be an open-for-all course, i.e. intersted participants from all over the world are welcomed to join. However, due to technical limination only HPI students are eligable for receiving their credits points in the course of their studies.
  • Fri Sep 25, 2020: Initial version of the lecture web page published. 

Slides

Slides will be available in a timely manner after the corresponding lecture.

Lecture slides (most recent at top)

  • CW07: Final exams are scheduled for Feb 16, 2021
  • CW06: Review of exercise III and Q&A is scheduled for Feb 11, 2021.
  • CW05: Guest lecturers (see details above)
  • CW04: Sensor data (slides) and unsupervised learning (slides)
  • CW03: Neural networks (slides)
  • CW02: Medical imaging (slides)
  • CW01: Intro to the med. use case infectious diseases and care (slides)
  • CW53: academic Christmas holidays
  • CW52: academic Christmas holidays
  • CW51: Genome data acquisition and processing (slides) and data management for precision oncology (slides)
  • CW50: Data science for precision oncology (slides) and text mining for biomedical knowledge discovery (slides)
  • CW49: Text data & ontologies (slides) and clinical natural language processing (slides)
  • CW48: Biology Recap (slides) and DNA mini exercise (slides)
  • CW47: Categories of digital health data (slides) and intro to the med. use case oncology (slides
  • CW46: Machine learning design process in digital health (slides) and software architectures for digital health (slides)
  • CW45: Kickoff lecture (slides) and administrative details of the lecture (video) << please use the access code for the video conference to access the video.
  • Teaser

How-To & Exercises

  • Final exam preparation (slides)
  • Instructions to access exercises (slides) and introduction to openHPI (slides).
  • Evaluation of Exercise I (slides)
  • Evaluation of Exercise II (slides)
  • Evaluation of Exercise III (slides)

Scope of the lecture

Welcome to the online class: we are very excited that you are interested in learning more about the foundations data management for digital health. A very relevant topic not only in times of worldwide COVID-19 pandemic. In this lecture, we will provide you specific examples from the field of digital health to understand where and how data is acquired, what are the challenges with these specific types of data, and how to handle them with latest technology advances. We will link to latest worldwide developments in fighting the COVID-19 pandemics and provide you with a better understanding of the latest decisions and developments, where applicable. 

After participating in the course, you will be equipped with the ability to: 

  • assess requirements of selected real-world use cases from the medical field,
  • select latest technology building blocks to create viable healthcare software solutions, and
  • analyze requirements for data analysis and processing, e.g. for machine learning.

In the course, we will have invited guest speakers sharing their real-world experience with you in a brief presentation. You will also have the chance to raise your questions and discuss with them in the course of the lecture.

Further details about the structure of the lecture will be shared in the first course of the lecture with you.
We are looking forward to e-meet you soon. 

Grading

You have to pass all intermediate exercises during the lecture prior to participate the final exam (Prüfungsvorleistung).

The final grading will be determined by the following parts:

  • Final exam at the end of the course (100%).