Manipulate the default connectome provided with TVB to see how structural lesions effect brain dynamics. In this hands-on session you will insert lesions into the connectome within the TVB graphical user interface (GUI). Afterwards, the modified connectome will be used for simulations and the resulting activity will be analysed using functional connectivity.
This presentation discusses the impact of data sharing in stroke.
This talks presents an overview of the potential for data federation in stroke research.
This talk focuses on the EAN Scientific Panel of Stroke, in particular on the aims and roles of the panel.
This lesson gives an introduction to the Mathematics chapter of Datalabcc's Foundations in Data Science series.
This lesson serves a primer on elementary algebra.
This lesson provides a primer on linear algebra, aiming to demonstrate how such operations are fundamental to many data science.
In this lesson, users will learn about linear equation systems, as well as follow along some practical use cases.
This talk gives a primer on calculus, emphasizing its role in data science.
This lesson clarifies how calculus relates to optimization in a data science context.
This lesson covers Big O notation, a mathematical notation that describes the limiting behavior of a function as it tends towards a certain value or infinity, proving useful for data scientists who want to evaluate their algorithms' efficiency.
This lesson serves as a primer on the fundamental concepts underlying probability.
Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.
This compilation is courtesy of freeCodeCamp.
This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.
This lesson was created by RootMath.
This lesson discusses both state-of-the-art detection and prevention schema in working with neurodegenerative diseases.
This lecture explains the concept of federated analysis in the context of medical data, associated challenges. The lecture also presents an example of hospital federations via the Medical Informatics Platform.
This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.
This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below.
This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics.
This is a tutorial on using the open-source software PRSice to calculate a set of polygenic risk scores (PRS) for a study sample. Users will also learn how to read PRS into R, visualize distributions, and perform basic association analyses.