HelloAI Professional RIS course
Making AI the superpower of medical professionals
To pre-register for the HelloAI Professional RIS course for free, click on the "Enrol" button, use the special promo code: HELLORISPRO and reserve your seat today!
Please note that this course is complimentary for RIS residents with a small admission fee of only 10 euros.
Your application will be evaluated by the Organizers, and access to the course will be activated based on your eligibility. Course materials will be available from the 20th of May until the 30th of August, 2022.
➡ Check your eligibility for the RIS scholarship here.
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
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
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. - Challenges and importance of data annotation
3.1. - Introducing AI solution in your Healthcare Provider organization
3.2. - Education, innovation and accelerator funding opportunities
3.3. - “Smartreport”– Explaining medical reports with the help of AI
3.4. - Secure operations verification
3.5. - GUIDE: Quick overview - Basics of ML and AI
3.6. - Introduction of KTH
3.7. - AI fundamentals
3.7.1 - AI fundamentals - Machine Learning Module
3.7.2 - AI fundamentals - Ontology Logic Module
3.7.3 - AI fundamentals - Deep Learning Module
Module 3 - Quiz 1 - AI Fundamentals
3.8. - Python and Google Colab
3.8.1 - GUIDE: Python notebook
3.8.2 - Python and Google Colab - Intro (Python codes included)
3.8.3 - Python and Google Colab - Variables
3.8.4 - Python and Google Colab - Operators
3.8.5 - Python and Google Colab - Data structures
3.8.6 - Python and Google Colab - Controll flow
3.8.7 - Python and Google Colab - Imports
3.8.8 - Python and Google Colab - Functions
3.8.9 - Python and Google Colab - Objects
4.1. - Why Data handling, preparing and distributed machine learning are needed?
4.2. - Image Analysis without AI
4.2.1 - Image Analysis without AI - Medical Images
4.2.2 - Image Analysis without AI - Gray-Scale and Texture Features
4.2.3 - Image Analysis without AI - Texture Features (cont)
4.2.4 - Image Analysis without AI - Shape features
4.3. - Machine Learning in Medical Image Analysis
4.3.1 - Machine Learning in Medical Image Analysis - Rule based AI vs machine learning
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 1
4.3.2 - Machine Learning in Medical Image Analysis - SVM and KNN
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 2
4.3.3 - Machine Learning in Medical Image Analysis - Decision tree and random forest
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 3
4.3.4 - Machine Learning in Medical Image Analysis - Image features
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 4
4.3.5 - Machine Learning in Medical Image Analysis - Machine learning examples
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 5
4.3.6 - Machine Learning in Medical Image Analysis - Machine learnings vs deep learning
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 6
4.3.7 - Machine Learning in Medical Image Analysis - ANN
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 7
4.3.8 - Machine Learning in Medical Image Analysis - CNN for image classification
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 8
4.3.9 - Machine Learning in Medical Image Analysis - Common CNN Architecture
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 9
4.3.10 - Machine Learning in Medical Image Analysis - FCN for image segmentation
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 10
4.3.11 - Machine Learning in Medical Image Analysis - Deep learning examples
Module 4 - Quiz 1 - Machine Learning in Medical Image Analysis - Lesson 11
4.4 - AI Insights by UM - D-Lab
4.4.1 - AI in imaging - The Example of handcrafted radiomics by UM
4.4.2 - AI in treatment personalization - by UM
4.4.3 - AI based decision support systems for improved healthcare - By UM
4.4.4 - How good is AI for image segmentation and how can you trust it?
4.5. - AI in practice - Laboratory session
4.5.1 - GUIDE: Laboratory Instruction
4.5.2 - AI in practice - Introduction to Colab
4.5.3 - AI in practice - KNN (code included)
Module 4 - Quiz 2 - Deep dive in AI technology - Lesson 1 - KNN
4.5.4 - AI in practice - SVM (code included)
Module 4 - Quiz 2 - Deep dive in AI technology - Lesson 2 - SVM
4.5.5 - AI in practice - Random Forest (code included)
Module 4 - Quiz 2 - Deep dive in AI technology - Lesson 3 - Random Forest
4.5.6 - AI in practice - Feature Extraction (code included)
Module 4 - Quiz 2 - Deep dive in AI technology - Lesson - Feature Extraction
4.5.7 - AI in practice - Deep Network (code included)
4.6 - Outlook: AI from the Lab to the installed Base - Industry insight
5.1. - How Artificial Intelligence is making health care more human
5.2. - You need a platform: Edison Digital Platform as start-up co-development model
5.3. - Follow my patient AI based solution in a HCP
5.4. - Value and benefits in providing a futuristic scalable roadmap for AI applications
Module 5 - Quiz 1 - Introduction Edison orchestrator
5.5. - Unlock data and unleash intelligence, effortlessly
5.6 - GUIDE: EHS tutorial
Module 5 - Quiz 3 - EHS tutorial