The ABC of AI: Basics of Deep Learning for Radiologists

In this radiology lecture, we introduce the basic concepts that every radiologist should know about deep learning and artificial intelligence in the context of medical imaging. In a pleasant and informative way, we will review the history of the development of this technology, and we will give a brief explanation of the terminology that is necessary to master in order to understand this technology, which is becoming more and more part of our daily work.

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Description

In this radiology lecture, we introduce the basic concepts that every radiologist should know about deep learning and artificial intelligence in the context of medical imaging.

In a pleasant and informative way, we will review the history of the development of this technology, and we will give a brief explanation of the terminology that is necessary to master in order to understand this technology, which is becoming more and more part of our daily work.

Learning Objectives

Explain the difference between AI, machine learning and deep learning Understand how deep learning is used in medical imaging Identify current clinical applications of AI in radiology Recognise the opportunities and limitations of AI tools Assess how AI may impact future radiology workflows and reporting

Topics Covered

To jump to a specific chapter, click on the chapter title once the video is playing.

00:14 - Introduction to Deep Learning for Radiologists

01:11 - Defining Intelligence and Its Challenges

03:06 - Historical Development of Artificial Intelligence

05:02 - Narrow vs. General AI

07:59 - Reasons Behind the Recent Explosion of AI

12:06 - Deep Learning and Machine Learning Paradigms

18:38 - Understanding Neural Networks and Perceptrons

22:12 - Training Neural Networks: Weights and Loss Functions

25:00 - Importance of Data Splitting in Machine Learning

31:00 - Conclusion and Future Challenges for AI in Radiology

Lecturers

Daniel Eiroa^M.D.

Spain

Daniel Eiroa is a Radiology Consultant and AI for Medical Imaging Specialist currently working at Primary Health Care Unit Barcelona Ciutat. FER-AIRP 2017 Fellowship Recipient. Dr. Eiroa has authored more than 50 communications, scientific articles and book chapters. He regularly participates in training sessions and lectures on AI and Medical Data Science.

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