Machine learning

My experience at the NordBioMedNet Summer School 2020

Hello everyone! This time I will talk about my experience at the summer school in Computational Biomedicine, Imaging, Machine Learning and Precision medicine. However, this year and due to the current situation, the summer school had to be held online instead of in person at the Seili archipelago. For this reason, I will discuss on this blog some of the most technical aspects of this short course. In addition, I will talk about the applications and impact that Computational Biomedicine and Bioimaging have on the clinical field.

What is NordBioMedNet summer school?

This is a summer school that lasts only one week (August 10 to 14) and has a very strong focus on the field of computational biomedicine combined with methods and techniques on bioimaging and machine learning. The school is organized in conjunction by University of Turku, University of Eastern Finland, University of Southern Denmark, University of Bergen and Karolinska Institutet. In the case of KI, the summer school applications are open for the master’s programmes in Biomedicine, Molecular Techniques in Life Science and Toxicology.

In addition, this short school has the aims of combining the different biomedical expertise areas from all participating Nordic universities into one intensive course and to promote internationalization among students and countries. Unfortunately, given the current circumstances, the course could not be held on the wonderful Seili archipelago in Finland ☹ and therefore had to be held online.

What was this year’s topic?

This year’s topic was on brain tumors, with a greater focus on glioblastoma clinical diagnosis. The aim of the summer school was to learn on brain tumor classifications, molecular aspects of glioblastoma, data analysis on magnetic resonance imaging (MRI) images and data training using machine learning techniques in order to improve diagnosis of this very aggressive brain cancer type.

What was the course about?

Although it was a very short and fast course, it was very intensive, and I can say that I learned quite a lot during this time. Moreover, it is important to highlight that before the course starts formally you are supposed to work on some pre-assignments which facilitate the learning process thru the course. To make easier to understand the summer school structure I will present a table divided in before and during summer school:

  Before (pre-assignments)  During
Bioethics modules: You must read and watch some video-recorded lectures on bioethics and then perform some exercises in which you analyze diverse controversial ethical casesDay 1: Lectures on brain tumor bioimage informatics and machine learning, clinical aspects on brain cancer and molecular aspects on glioblastoma  
Reading papers: You must read a couple of scientific articles on the topic, in this case brain cancer, so you get familiar with the clinical and molecular aspectsDay 2: Workshop on image analysis using machine or deep learning methods to train image data. The whole workshop is carried out using Python  
Overleaf online editor: You must orientate yourself on how to use this online editor given that it will be the edition tool you and your group will use to present the final projectDay 3: Workshop in Bioethics, in which you must discuss an ethical case with your group, the lectures and the whole class
Install Python: Given that machine learning and image analysis will be mostly done with Python, you must install it and if you are not very familiar with it (like me) you can perform a couple of exercise so you get familiar with this coding language   Day 4: Lectures on Euro-Bioimaging and on career opportunities outside academia at which you get to know some bioinformatics companies  
 Day 5: Project presentations by group. The last day we must present our project outlines in which we explain what we want to evaluate and diagnostically improve using data analysis and machine learning tools  
 Afternoons: During the week, you and your group must work on the design and structure of your project

Computational Biomedicine and Bioimaging applications and impact

Nowadays, there are many different companies worldwide that are implementing bioimaging and machine learning to their biomedical technologies to improve clinical diagnosis on patients with aggressive cancer types or reoccurring cancers. For this reason, NordBioMedNet has done an excellent job at giving us an overview of how these new computational tools work and how they are applied to the clinical field. Besides, this summer school presents us some of the job opportunities we can have on this field. In conclusion, bioimaging and machine learning are computational tools that are gaining importance on the medical field because they have proven to be effective at diagnosing rare types of brain cancer and have also allowed physicians to give better treatments to these patients.  

My experience

This summer school was a whole new experience to me mostly because of the school’s topic. I must say that despite the circumstances I enjoyed it and I learned a lot of new stuff, especially on the machine learning topic. However, it was a bit disappointing that I missed the great chance of spending the course on the Seili archipelago, that for what I have seen and read, it is a wonderful place. I can also say that I meet wonderful people (my group members) and that I had a very nice time chatting with them. 

Finally, I want to say that the only part that was terribly hard and that in my opinion did not flow as it was supposed (mostly because of the conditions) was the workshop on Python language. This was because I had no experience at coding, the machine learning topic is very complex, and the workshop was going super fast because we had to cover so many things in only few hours.


I hope this blog inspires you to apply for the next summer school (hopefully held in person next year) and that you are ready to challenge yourself to learn computational biomedicine and imaging.


Aline Colonnello Montero

Aline Colonnello - Toxicology

Aline Colonnello - Toxicology

My name is Aline Colonnello Montero, I am twenty five years old and I come from the wonderful but busy Mexico City. I consider myself to be a perseverant person who works hard to meet all my goals and ambitions. I have a bachelor’s degree in Biology and I currently study the Master’s programme in Toxicology at Karolinska Institutet. My job as part of the digital ambassadors’ team consists on writing blogs


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