Data Management for Digital Health 2020

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.

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. Furthermore, you will have the chance to gather hands-on experience.

Selbststudium
Kurssprache: English

Kursinformationen

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.

Lernmaterial

  • OpenHPI Test Quiz

  • DM4DH Exercise I:

    Covered Topics: Actors in Healthcare, Iterative Machine Learning Design Process, Software Architectures, Categories of Data.
  • DM4DH Exercise II:

    Covered Topics: Medical Use Case Oncology, Bio Recap, Text Data & NLP.
  • DM4DH Exercise III:

    Covered Topics: Genome Sequencing and Processing, Medical Imaging, Machine Learning for Digital Health, Sensor Data.

Für diesen Kurs einschreiben

Der Kurs ist kostenlos. Legen Sie sich einfach ein Benutzerkonto auf openHPI an und nehmen Sie am Kurs teil!
Jetzt einschreiben

Lernende

Aktuell
Heute
67
Kursende
31. März 2021
66
Kursstart
2. November 2020
3

Anforderungen für Leistungsnachweise

  • Den Leistungsnachweis erhält, wer in der Summe aller benoteten Aufgaben mindestens 50% der Höchstpunktzahl erreicht hat.
  • Die Teilnahmebestätigung erhält, wer auf zumindest 50% der Kursunterlagen zugegriffen hat.

Mehr Informationen finden Sie in den Richtlinien für Leistungsnachweise.

Dieser Kurs wird angeboten von

Dr. Matthieu-P. Schapranow

Dr. Matthieu-P. Schapranow ist Manager des Programms „E-Health“ am Hasso-Plattner-Institut, Gastwissenschaftler am Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) des U.S. Department of Veterans Affairs und an der Charité – Universitätsmedizin Berlin. Darüber hinaus engagiert sich ehrenamtlich u.a. in der Berliner Krebsgesellschaft, im Bundesverband Informationswirtschaft, Telekommunikation und neue Medien e.V. (BITKOM) in der Arbeitsgruppe e-Health, sowie in der Global Alliance for Genomics and Health. Dr. Schapranow wurden die wissenschaftlichen Abschlüsse Dr.-Ing., M.Sc., sowie B.Sc. in Software Engineering verliehen. Er wurde u.a. ausgezeichnet mit dem Personalized Medicine Award Convention 2015, dem European Life Science Award 2014, sowie dem Berlin-Brandenburger Innovationspreis 2012. Anlässlich des “World Health Summit 2013“ veröffentlichte Dr. Schapranow gemeinsam mit Prof. Dr. Plattner das Buch „High-Performance In-Memory Genome Data Analysis”