Would you like to learn the basics of Machine Learning to incorporate it into your research daily clinical practice and research projects? In this online fellowship you will acquire knowledge about how a convolutional neural network works, being able to experiment in real time with the main parameters that influence its training.
Too late? Dont worry, Join us on our next edition of this course 5 7 Sept 2023 with Daniel Eiroa ONLINE Practical Deep Learning for Radiologists Fellowship
The upsurge of Machine Learning and Deep Learning algorithms paired with the high amount of digital data generated in radiology is changing this medical specialty. Deep Learning algorithms, in particular convolutional networks, are promising techniques for processing medical imaging data in a wide variety of clinical scenarios.
The first session will be focused on data acquisition and manipulation in order to optimize for a Deep Learning task, what the main hindrances are and how to solve them. We will also cover the basic requirements and tools needed for DL in the radiology setting.
The second session will cover a hands-on neural network training pipeline in which we will tweak the parameters of a neural network to understand how they influence the final result. We will also provide tips and advice on how to start the DL journey in your own department.
The last session will be dedicated to model evaluation, how the main metrics are useful in different case scenarios, and their limitations in a “real-life” clinical setting. We will also review and work on the guidelines for critical assessment of AI research.
Throughout the course we will also see other applications of DL in the healthcare setting, such as study protocolization, structured reporting and communication of incidental findings, among others.
We will also cover the main limitations of Deep Learning in the field of medical imaging and discuss basic notions and resources to start experimenting with Deep Learning algorithms in the daily clinical practice. Each day, a series of selected topics will be presented, followed by a guided interactive activity and group discussion. At the end of every session, we will take some time to explain and debate Deep Learning implementation scenarios in the field of Radiology.
Level II - General radiologist
Daniel Eiroa is a Radiology Consultant and Data Analyst currently working at Vall d'Hebron Barcelona Hospital Campus. 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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TMC Academy offers a 7-day money back guarantee from the moment of the online fellowship purchase.
How do I request a refund?
Send us an email at academy.info@telemedicineclinic.com and we will process your refund.