Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI
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Data Management for Digital Health (Wintersemester 2020/2021)

Dozent: Dr.-Ing. Matthieu-Patrick Schapranow (Digital Health - Personalized Medicine)
Tutoren: M.Sc. Florian Borchert
Website zum Kurs: https://hpi.de/digital-health-cluster/teaching/archive/winter-term-2020-21/data-management-for-digital-health.html

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.10.- 20.11.2020
  • Lehrform: Vorlesung / Übung
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
  • SCAD: Scalable Computing and Algorithms for Digital Health
    • HPI-SCAD-C Concepts and Methods
  • SCAD: Scalable Computing and Algorithms for Digital Health
    • HPI-SCAD-T Technologies and Tools
  • DICR: Digitalization of Clinical and Research Processes
    • HPI-DICR-C Concepts and Methods
  • DICR: Digitalization of Clinical and Research Processes
    • HPI-DICR-T Technologies and Tools
  • APAD: Acquisition, Processing and Analysis of Health Data
    • HPI-APAD-C Concepts and Methods
  • APAD: Acquisition, Processing and Analysis of Health Data
    • HPI-APAD-T Technologies and Tools

Beschreibung

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. 

More about the course

Leistungserfassung

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%).

Termine

  • Schedule: 
    • Tuesdays 11.00am (s.t.)
    • Thursdays 09.15am (s.t.) 
  • First course: 
    • Tuesday Nov 3, 2020 at 11.00am via Web Meeting

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