Technology

New age of dementia treatment

Although multifactorial diseases have high survival rate, we are still far away from any cures.  In fact most of them don't have cures. We will accelerate advancement by using highly sophisticated technology and enhance the quality of lives as well as exceed the current benchmark of disease research progress.  The purpose will be to learn from experience and act by instruction.  It will adapt to the environment, and the environment by situation in reciprocal, influence its behaviour.

Loic Merckel
Investment in prevention of disease is much more efficient and cheaper than treatment itself...
technology

Machine learning helping in a big way

Research, combined with patient’s data collected from over the years or big data, is more relevant and accurate than a research itself. Our cognitive machine takes the data and through learning techniques it identifies patterns that give accuracy in prevention. With the big data and incremental iterations of cases, the computer can build its knowledge of multifactorial diseases, a list of causes, the strength of the cause indication and it can also provide a personalized prevention measures with possible solutions.
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It’s simple – research, combined with patient’s data collected from over the years or big data, is more relevant and accurate than a research itself. Our cognitive machine takes the data and through learning techniques it identifies patterns that give accuracy in prevention. With the big data and incremental iterations of cases, the computer can build its knowledge of multifactorial diseases, a list of causes, the strength of the cause indication and it can also provide a personalized prevention measures with possible solutions. Although multifactorial diseases have high survival rate, we are still far away from any cures. In fact most of them don't have cures. We will accelerate advancement by using highly sophisticated technology and enhance the quality of lives as well as exceed the current benchmark of disease research progress. The purpose will be to learn from experience and act by instruction. It will adapt to the environment, and the environment by situation in reciprocal, influence its behaviour. Every single one of us is an original and everything that happens in our lives affects our individual DNA more than we ever thought. Our goal is to offer each client personalized approach using artificial intelligence and most recent technology in DNA analysis. We must understand that artificial intelligence allows searching the data interactions that would otherwise have escaped scientists view.
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technology

Artificial intelligence system in our hands

The use of neural networks in the prediction of Alzheimer’s disease, based on the analysis of the results of genetic analysis, is our approach. Thus a suitably selected neural network can be taught a set of real data. Such selected neural networks will then learn to differentiate subjects and distribute them into groups of controls and patients while evaluating and quantifying the disease risk. The advantage of this approach compared with a calculation by OR or RR by conventional methods is that neural networks work in an unbiased non-prejudicial manner, independently of researchers, analyzing the given set of data and looking for relationships that could quite possibly escape the attention of researchers.
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The use of neural networks in the prediction of Alzheimer’s disease, based on the analysis of the results of genetic analysis, is our approach. Thus a suitably selected neural network can be taught a set of real data. Such selected neural networks will then learn to differentiate subjects and distribute them into groups of controls and patients while evaluating and quantifying the disease risk. The advantage of this approach compared with a calculation by OR or RR by conventional methods is that neural networks work in an unbiased non-prejudicial manner, independently of researchers, analyzing the given set of data and looking for relationships that could quite possibly escape the attention of researchers.

Machine learning data techniques give effective solutions to harness those data and find non-trivial patterns that are strong predictors of probable and undesirable future outcomes. The labeled data are used to train machine learning algorithms so as to accurately predict the probable future outcome of new clients. Artificial neural networks together with decision trees learning are combined to achieve better predictive performances.
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Jan Ruzicka
"We know it´s ambitious. Our aim is to fight degenerative diseases. And the important part is - we won´t stop until we win."
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Al Pineda
"By following our treatment scheme, people can delay the onset of disease and prolong a healthy life."
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Collaboration

Exciting journey ahead of us all

We are actively looking for partners with similar visions, who can join forces and collaborate with us along the way.

Get in touch

We are proud members of
the University of Cambridge

Headquarters

Aequa Sciences Ltd.
London

71-75 Shelton street
London, WC2H 95G
England
Laboratories

Aequa Sciences labs
Brno

Rokycanova 4437/5
61500 Brno
Czech Republic

Thank you for your interest in Aequa Sciences.

If you would like to work with us or simply receive more information about our project, please fill in your contact details below and we will get back to you.