Machine Learning for Mobile Health
An introducation to artificial intelligence and the concepts of mobile health
Julius-Maximilians-University Würzburg (JMU), Institute for Clinical Epidemiology and Biometry, medical informatics
Mobile Health (mHealth) and Machine Learning are both topics that have become very popular in recent years due to the availability of mobile data, sensors, and more computational power of local machines. The widespread adoption of smartphones creates an enormous potential to improve healthcare services. More than 17,000 mHealth apps now are available for smart phones and other devices, and they do everything from monitoring urine flow for patients with enlarged prostates to reminding people prone to kidney stones to drink more water. mHealth has a tremendous potential to change health care, and artificial intelligence is a key element for it.
Target Group: The course is aimed at medical students, physicians or medical scientists and computer science students.
Learning Objectives: The participants of this course will get an introduction to both mobile health and machine learning. They will learn how to use Python libraries such as as scikit and pandas on a beginner level.
Embedding: This course will be run as a HiGHmed module only.