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Join Ads Marketplace to earn through podcast sponsorships.
Manage your ads with dynamic ad insertion capability.
Monetize with Apple Podcasts Subscriptions via Podbean.
Earn rewards and recurring income from Fan Club membership.
Get the answers and support you need.
Resources and guides to launch, grow, and monetize podcast.
Stay updated with the latest podcasting tips and trends.
Check out our newest and recently released features!
Podcast interviews, best practices, and helpful tips.
The step-by-step guide to start your own podcast.
Create the best live podcast and engage your audience.
Tips on making the decision to monetize your podcast.
The best ways to get more eyes and ears on your podcast.
Everything you need to know about podcast advertising.
The ultimate guide to recording a podcast on your phone.
Steps to set up and use group recording in the Podbean app.
The future of healthcare – Keep people healthy with innovative health appliances and technologies
There has been a lot of discussion about the importance of good health and well-being, especially as the world population rises and at the same time life expectancy is increasing. The fast-growing cost of acute care are pushing the healthcare systems worldwide to a limit. So, healthcare increasingly places great emphasis on enhancing well-being to prevent illness rather than sporadically treating acute illnesses. The IoT has great potential to support good health and well-being. With smart electronic devices, either worn on the body or even installed at home, it is possible to measure people's fitness and health status and trigger appropriate actions. Here, data mining, algorithms, machine learning and artificial intelligence play a central role so these topics have received a lot of attention in medical research recently. This is what we want to talk about with our guest today. Professor Björn Eskofier is heading the Machine Learning and Data Analytics Lab of the Friedrich-Alexander-Universität Erlangen-Nuremberg. Currently, this lab has about 50 co-workers in the field of machine learning and signal analysis for wearable computing systems with a focus on sports and healthcare.
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