Digicampus
Vorlesung: Digital Health - Details
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Lehrveranstaltung wird online/digital abgehalten.

Allgemeine Informationen

Veranstaltungsname Vorlesung: Digital Health
Veranstaltungsnummer INF-0380
Semester SS 2021
Aktuelle Anzahl der Teilnehmenden 42
Heimat-Einrichtung Embedded Intelligence for Health Care and Wellbeing
Veranstaltungstyp Vorlesung in der Kategorie Lehre
Erster Termin Dienstag, 13.04.2021 12:15 - 13:45, Ort: (lecture video will be uploaded)
Online/Digitale Veranstaltung Veranstaltung wird online/digital abgehalten.
Hauptunterrichtssprache englisch
Literaturhinweise Panesar, A (2019): Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes. Coventry, UK: Apress.

Further literature is going to be announced during the lecture.
ECTS-Punkte 5

Räume und Zeiten

(lecture video will be uploaded)
Dienstag, 13.04.2021, Dienstag, 20.04.2021, Dienstag, 27.04.2021, Dienstag, 04.05.2021, Dienstag, 11.05.2021, Dienstag, 18.05.2021, Dienstag, 01.06.2021, Dienstag, 08.06.2021 12:15 - 13:45
Dienstag, 15.06.2021 12:15 - 13:00
Dienstag, 22.06.2021, Dienstag, 29.06.2021, Dienstag, 06.07.2021, Dienstag, 13.07.2021 12:15 - 13:45
(Live Session: Please join the Zoom meeting)
Dienstag, 15.06.2021 13:00 - 13:45

Kommentar/Beschreibung

Digital health is the use of information and communication technology for disease prevention and treatment. Students will get to know the key concepts, definitions, and technologies in the field of digital health. They will get insights into acceptability and usability of digital health applications in the context of various diseases. Students will get to know strategies for collecting medically-relevant data of various modalities, e.g., recording speech data using microphones or tracking heart rate via wearable sensors, and learn about principal concepts of intelligent biosignal processing and analysis including feature extraction and machine learning in the context of healthcare applications. Students will gain competence in selecting appropriate methodology or designing new approaches for a broad range of health-related signal processing and analysis tasks. Finally, students will be made familiar with current and potential future implications of intelligent biosignal analysis to the health sector as well as sensitised to related ethical and data privacy aspects.