Author: justoh

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IBM Global University Programs launches new courses free for students and faculty in academic institutions

IBM Global University Programs is pleased to announce the launch of 3 new IBM Academic Initiative approximately 2-hr micro-credential courses in healthcare covering the following topics:
Improving Healthcare:  The Role of Artificial Intelligence (AI) – httpa://ibm.biz/ai-in-healthcare
The individual completing this course will have demonstrated knowledge and understanding of an overview of AI in healthcare through use cases and understanding the benefits, barriers to adoption, challenges to implementation, and the role of ethics in AI.
Improving Healthcare:  The Role of Data Analytics and Data Science – https://ibm.biz/ds-in-healthcare
The individual completing this course will have demonstrated knowledge and understanding of the foundation of data science in healthcare including the following:  the data explosion, key definitions and how healthcare is a Big Data repository, uses cases in healthcare, and how Big Data integrates with new and emerging technologies.
Improving Healthcare:  The Role of Cloud Computing – https://ibm.biz/cloud-in-healthcare
The individual completing this course will have demonstrated knowledge and understanding of the foundation of cloud computing in healthcare including trends/pressures facing healthcare as well as the cloud delivery models and service types and use cases of cloud computing in healthcare.
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Reflections upon Deep Learning for Medical and Industrial Imaging – an online networking event

Reflections upon Deep Learning for Medical and Industrial Imaging – an online networking event

Deep Learning for Medical and Industrial Imaging networking event was organized online this spring. Originally, we (KUBIAC personnel and guys from the Department of Applied Physics – special thanks goes to Timo Lähivaara)  planned to organize this event as a normal face-to-face event but a virus messed up that plan.  So we decided to go online.

This proved out to be a very successful move. We had an audience of 102 persons, something that would not have been possible in a face to face meeting. From the 121 persons who registered to the event, the majority was from UEF, but there were many registrants from Kuopio University Hospital (24 registrants ), local companies, Savonia and other universities in Finland. The feedback from the professionals working in the Kuopio University Hospital indicated that they would not have been able to participate in a face to face seminar.

Few technical problems aside, the presentations and also the discussion flowed surprisingly well. Of course, the discussion between 100 persons online is not the same as it would be in a face to face meeting, but we actually managed to have a pretty solid discussion session that the undersigned enjoyed much but had to break the discussion at the half-hour mark because of the start of another event.

We collected written feedback – online of course.  Based on the feedback, participants liked the online event and were hungry for some more.  A summary of the feedback is as follows (5 stars is the maximum):

I found the webinar useful:  4.38 stars on average

I learned something new: 4.13 stars on average

The topic of the webinar was interesting: 4.71 stars on average

The presentations were easy to follow:  4.13 stars on average

The concept of online webinar worked well: 4.54 stars on average

We also got many good ideas based on the feedback provided. Thanks!

 

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Deep Learning for Medical and Industrial Imaging – an online networking event

Deep Learning  for Medical and Industrial Imaging – an online networking event

Organized jointly by Kuopio Biomedical Image Analysis Center and Department of Applied Physics

Registration  (free of charge)

14th May 2020 12.00 – 14.15

Deep learning is re-shaping the analysis approaches used for industrial and (bio)medical imaging. This online webinar/networking event introduces recent advances in the development of deep learning applications in Kuopio area. By this event, we hope to recognize new synergies in this research area, both in methodological and application perspectives. Each presentation is 10 minutes followed by 5 minutes of discussion.  The event concludes with general discussion in which it will possible to interact with individual presenters.  The link to the event will provided later.

Program

12.00 – 12.15 Jussi Tohka, “Biomedical Image Analysis Method Development at UEF, KUBIAC image Analysis Center”

12.15 – 12.30 Riccardo De Feo “Deep learning fundamentals”

12.30 – 12.45 Juan Miguel Valverde “Image segmentation using convolutional neural networks”

12.45 – 13.00 Timo Lähivaara “Simulation based deep neural networks for wave problems”

13.00 – 13.15 Robert Ciszek “Deep learning for reconstruction of  MR images”

13.15 – 13.30 Timo Leppänen ““Neural network analysis of sleep recordings – potential to fully automatized diagnosis of obstructive sleep apnea”

13.30 – 13.45 Sami Väänänen/Tomi Nissinen “Dual-energy x-ray absorptiometry (DXA) image datasets and current projects in UEF and KUH for machine learning based osteoporosis diagnostics”

13.45 – 14.15 Discussion