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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

Guidelines