HelloAI Professional RIS Scholarship course
Making AI the superpower of medical professionals
HelloAI Professional RIS Scholarship course focuses on advanced AI concepts and the application of customized solutions using various tools and methodologies. Students will advance their skills in scaling AI solutions and effectively presenting them to healthcare organizations.
This EIT Health-labeled program combines theoretical AI presentations with hands-on practical workshops.
Join this course to delve into fascinating and challenging AI topics that you may have heard of but haven't had the opportunity to professionally educate yourself on, further advancing your career.
➡ Make sure to check your eligibility and the conditions of the RIS scholarship here.
Full scholarship (administration fee is required) for RIS citizens
Insights on the outcomes AI can bring to HCP institutions after the initial investment
When and why can you trust the “Black Box” & understand the nature and implications of algorithm bias
Unveil how AI becomes the critical toolkit in making healthcare sustainable and effective (practical case studies)
See real-life examples of peer institutions and providers on how AI enhances the quality and efficacy of care of successful AI implementation (including insight on challenges)
Discover a roadmap of which areas shall be tackled in your organization to make AI implementation successful
Understand the benefits and opportunities of data-driven healthcare
Learn about technology diplomacy that will ease global alignment of AI governance and a vibrant innovation system
HelloAI Welcome Brochure
How to access your ECTS credit
How to access your EITH certificate
1.1 - AI, Personalized medicine and rethinking design
1.2. - Radiology powered by AI
1.3. - AI implementation in clinical environment
1.4. - Transforming healthcare with AI
1.5. - AI Application in Ultrasound
2.1. - Outlook: Start-up journey and acceleration, professional speech is important
2.2 - From scienticif idea to product - A startup journey
2.3. - Introduction of LEITAT Technology Center
2.4. - AI Product development cookbook
2.4.1 - GUIDE: Data Science Cookbook
Module 2 - Quiz 1 - Data Science Cookbook
2.5 - Outlook: AI from the Lab to the installed Base - Industry insight
3.1. - Introducing AI solution in your Healthcare Provider organization
3.2. - Why Data handling, preparing and distributed machine learning are needed?
3.3. - “Smartreport”– Explaining medical reports with the help of AI
3.4. - AI Insights by UM - D-Lab
3.4.1 - AI in imaging - The Example of handcrafted radiomics by UM
3.4.2 - AI in treatment personalization - by UM
3.4.3 - AI based decision support systems for improved healthcare - By UM
3.5. - Introduction of KTH
4.1. - Python and Google Colab
4.1.1 - GUIDE: Python notebook
4.1.2 - Python and Google Colab - Intro (Python codes included)
4.1.3 - Python and Google Colab - Variables
4.1.4 - Python and Google Colab - Operators
4.1.5 - Python and Google Colab - Data structures
4.1.6 - Python and Google Colab - Controll flow
4.1.7 - Python and Google Colab - Imports
4.1.8 - Python and Google Colab - Functions
4.1.9 - Python and Google Colab - Objects
5.1. - Image Analysis without AI
5.1.1 - Image Analysis without AI - Medical Images
5.1.2 - Image Analysis without AI - Gray-Scale and Texture Features
5.1.3 - Image Analysis without AI - Texture Features (cont)
5.1.4 - Image Analysis without AI - Shape features
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