Created with Sketch.
EUSOMII on AIR
32 minutes | Jan 13, 2021
Episode 6, Jan. 2021 - Interview with Prof. Emanuele Neri, co-founder of EuSoMII
In this first 2021 episode of EuSoMII on Air, Shah Islam and Merel Huisman interview Prof. Emanuele Neri (University of Pisa), who is one of the co-founders of EuSoMII about the early days of EuSoMII and the way imaging informatics was introduced as a well-defined domain of expertise in the European landscape of radiology. Prof. Neri also tells us about the significance and value of the ongoing A.I. revolution that is taking place within the profession of radiology, and the importance of including basic knowledge about A.I. into the European Training Curriculum, for training the new generation of radiologists.
32 minutes | Sep 14, 2020
Episode 5 - Why radiologists should be bilingual when using A.I.
EuSoMII talks with Matthew Lungren, Associate Professor at Stanford University Medical Center and co-director of Stanford Center of Artificial Intelligence in Medicine and Imaging (AIMI). Interviewers: Erik Ranschaert and Merel Huisman from EuSoMII - September 14, 2020 Topic: Importance of knowledge of fundamental principles of AI for both radiologists and radiology residents (trainees).
27 minutes | Jun 19, 2019
Episode 4 - The Medical Doctor as Data Scientist. Interview with dr. Bart-Jan Verhoeff.
For Episode 4 we interviewed doctor Bart-Jan Verhoeff, who's a nephrologist, a medical doctor specialized in kidney diseases. He works at the St. Jansdal Hospital in Harderwijk, the Netherlands, where he’s also CMIO or Chief Medical Information Officer. He’s also known as dokter.ai, from the blog carrying the same name. He trained himself in machine learning to develop an algorithm able to predict the likelihood of re-uptake of his patients. Verhoeff emphasizes the usefulness of machine learning as a method of using patient data intelligently. By using models based on data from the Electronic Patient Rrecord (EPR), doctors can make predictions, so that they can improve work processes, and improve the quality of patient care. Please stay tuned and listen to this interesting 30 minute interview.
39 minutes | Apr 1, 2019
Episode 3 - Interview with Jonathan Berte, CEO of Robovision
Jonathan Berte is the founder and CEO of Robovision, a turnkey AI solution provider, with a powerful deep learning platform called RVAI. The company is specialized in deep learning-based machine vision and robot programming and is focused on the design, development and deployment of complete automation processes, where illumination, digital cameras, robots and artificial intelligent agents play an important role. Since recently the company has also become active in the medical field for labeling radiological images in the development of DL algorithms. The RVAI platform is not only able of speeding up the labeling process thanks its learning ability making it possible to automise the segmentation process, but it also allows its users including radiologists without any deep learning software skills to develop algorithms Please follow us in this exciting interview, which will undoubtedly open the eyes of those who are eager to learn more about what the future can and will bring us.
15 minutes | Mar 2, 2019
Episode 2 - ECR 2019 Interview with Prof. Bram van Ginneken
ECR 2019 Interview with Prof. Bram van Ginneken about A.I. for medical imaging. He explains his vision as physicist on the new developments in deep learning, and explains the reasons why radiologists should adapt and address the upcoming changes in their profession as a team.
14 minutes | Feb 28, 2019
Episode 1 - ECR 2019 Interview with dr. Hugh Harvey
For this first podcast during the ECR 2019 meeting in Vienna, we were able to interview Hugh Harvey about Artificial Intelligence in radiology, Listen to this 15 minute fascinating discussion about Artificial Intelligence in radiology: how should radiologists use it, how will the market develop, and what should radiologists do? Please share it if you like it.
Terms of Service
Do Not Sell My Personal Information
© Stitcher 2022