Search, Read and Judge Scientific Literature (Sommersemester 2019)
Dozent:
Prof. Dr. Erwin Böttinger
(Digital Health - Personalized Medicine)
,
Ariane Morassi Sasso
(Digital Health - Personalized Medicine)
,
Jan-Philipp Sachs
(Digital Health - Personalized Medicine)
,
Suparno Datta
(Digital Health - Personalized Medicine)
,
Daniel Lewkowicz
(Digital Health - Personalized Medicine)
Allgemeine Information
- Semesterwochenstunden: 2
- ECTS: 3
- Benotet:
Ja
- Einschreibefrist: 01.04.-26.04.2019
- Lehrform: Seminar
- Belegungsart: Wahlpflichtmodul
- Lehrsprache: Englisch
- Maximale Teilnehmerzahl: 30
Studiengänge, Modulgruppen & Module
- 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
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-S Specialization
- 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
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-S Specialization
- 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
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-S Specialization
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
Beschreibung
In this course, you will learn how to deal with scientific literature. The seminar will cover strategies for both the health and the computer science domain and be hands-on and interactive. You will learn and practice, how to search for and access relevant literature. Furthermore, you will apply strategies to read them in a smart and efficient way. In the format of a journal club, we will also read papers together, discuss them and evaluate their scientific solidness.
Leistungserfassung
- Weekly Assignments (not graded but mandatory)
- Final Report Evaluating a Digital Health Paper (100% of final grade)
Termine
Tuesdays 5 pm, G3.E 15/16
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