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Video lecture on person identification based on keystroke dynamics
21 July 2016

We have just uploaded a short video lecture about our work on person identification based on keystroke dynamics. See our page containing resources related to typing dynamics.

Classification of fMRI data using Dynamic Time Warping based functional connectivity analysis
15 July 2016

We are happy to announce that our recent work titled A model for classification based on the functional connectivity pattern dynamics of the brain has been accepted for publication in the proceedings of the Third European Network Intelligence Conference (ENIC 2016) and it will be presented at the conference. See you there!

Challenge - person identification based on keystroke dynamics
10 June 2016

We are happy to announce an open challenge on person identification based on keystroke dynamics! Person identification is essential in various online services such as banking or online exams. Typing dynamics is a simple biometrics that allows user identification. In order to successfully apply user identification based on keystroke dynamics, machine learning is required. In order to encourage research in this important domain, we announce an open challenge.

Collaboration with researchers of the Babes-Bolyai University
10 June 2016

Together with researchers from the Babes-Bolyai University in Cluj Napoca, we aim to explore how community detection techniques can be used to find communities of brain regions. We analyse the community structure under various conditions, such as different phenotypes, presence or absence of a disease, addiction, etc. On the long term, such an analysis may contribute to better understanding the phenomena and mechanisms underlying various diseases and phenotypes. First results of this collaboration will be presented at the 14th International Conference on Parallel Problem Solving from Nature and they will appear in the proceedings of the conference.

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Welcome to the BioIntelligence Site!

Our mission

With biointelligence we mean a multidisciplinary field of science: biointelligence is where machine learning meets biology and medicine.

In the last decades, biology transformed into a data rich science. The giant amount of biomedical data originating from various sources such as DNA sequencing, computer tomography (CT), magnetic resonance imaging (MRI), microarrays, magnetoencephalography (MEG), electroencephalography (EEG), electrocardiography (ECG), textual descriptions, etc., may often be used directly to address biomedical challenges. In most cases, however, advanced analytic techniques are required, including approaches based on machine learning. This is challenging because the straightforward application of machine learning is likely to lead to suboptimal results. Instead, adaptation of the methods and, in many cases, development of new approaches is required. This is a complex process involving the integration of biomedical knowledge into the analytic algorithms.

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...who contributed to the content appearing on the biointelligence site.

Krisztian Buza, PhD
principal investigator of the "BioMining" project

Júlia Koller, MD

Kristóf Marussy
junior researcher

Mararu Vlad
junior researcher

Ladislav Peska
junior researcher

Dóra Neubrandt
junior researcher


Krisztian Buza
e-mail: buza (at) biointelligence (dot) hu
phone: +36 20 912 74 26