Machine Learning for Health: Bridging the Gap between Research and Practice

Veranstaltet von Zühlke Zürich Meetup (https://www.meetup.com/de-DE/Zuhlke-Zurich-Meetup/events/270899096/)

You have to register for the event: https://register.gotowebinar.com/register/1773650101719810572

Machine Learning for Health: Bridging the Gap between Research and Medical Practice

Methods from the fields of Machine Learning and Artificial Intelligence have been applied successfully in many different domains and industries. The health sector is no exception to this. The digitisation of medical records and diagnostic data along with the increasing amount of patient generated data have placed high hopes when it comes to healthcare Machine Learning solutions.

As of today, no clear norms or guidelines for the development of AI devices in the medical field exist. Due to this and despite regular publications of papers on medical AI, only few approved applications of AI can be found in the medical practice. This is unfortunate, as AI has a great potential to curb rising healthcare costs and improve patient experience.

In this Webinar we will show how AI projects can be executed in a regulated setting. We will talk about the specifics of a medical Machine Learning project and how the Data Science Process needs to be adapted at each phase to satisfy regulatory requirements. We will cover the following topics for AI in health:

• Example Applications: Computer Vision, NLP and Time Series
• Norms & Guidelines
• Verification & Validation
• Software Development Process
• Data Science Process & Best Practices
• Explainable AI

Speakers:

Dr. Gabriel Krummenacher, Lead Data Science Team at Zühlke Engineering AG
Uwe Szymanski, Lead Architect Embedded Software at Zühlke Engineering AG