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.

Self-paced
Language: English

Course information

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.

Course contents

  • 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.

Enroll me for this course

The course is free. Just register for an account on openHPI and take the course!
Enroll me now

Learners

Current
Today
67
Course End
Mar 31, 2021
66
Course Start
Nov 02, 2020
3

Certificate Requirements

  • Gain a Record of Achievement by earning at least 50% of the maximum number of points from all graded assignments.
  • Gain a Confirmation of Participation by completing at least 50% of the course material.

Find out more in the certificate guidelines.

This course is offered by

Dr. Matthieu-P. Schapranow

Dr. Matthieu-P. Schapranow is Program Manager E-Health at the HPI, Visiting Scientist at the Mass. Veterans Epidemiology Research and Information Center (MAVERIC) of the U.S. Department of Veterans Affairs and at Charité – University Medicine in Berlin, Germany. He is a valued member of the Berlin Cancer Society contributing to the Federal Association for Information Technology, Telecommunications and New Media (BITKOM) and the Global Alliance for Genomics and Health. Dr. Schapranow holds a PhD as well as the MSc and BSc degrees in Software Engineering. He was honored with the Personalized Medicine Convention Award 2015, the European Life Science Award in 2014, and the Innovation Award of the German Capital Region in 2012. Together with Prof. Dr. Plattner, he published the textbook "High-Performance In-Memory Genome Data Analysis" in 2013.