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Artificial intelligence for healthcare.

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MicrobeLink

The replication of human intellectual processes by machines, particularly computer systems, is known as artificial intelligence. The fundamental objective of health-related artificial intelligence applications is to investigate the relationships between preventative or therapeutic methods and patient outcomes. We employ artificial intelligence algorithms in a variety of procedures, including diagnosis, the formulation of treatment protocols, drug discovery, personalized medicine, and patient monitoring and care.

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Proteome2Pathogen Application

In collaboration with TNO scientific team (led by Dr. Armand Paauw), we have developed framework to enable reliable identification of microorganisms, potentially causing human infectious disease. The identification is based on analysis of the bacterial proteome.

The developed application relies on a two-step workflow: a genus-level search followed by a species-level search. This strategy enables the rapid identification of microorganisms based on the analyzed proteome. Thus far, this method has mainly been validated using bacteria from simulated blood culture flasks (Berendsen et al. IJMM, 2019, Berendsen et al. Future Micro. 2017).

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SymbAIose computational framework

As machine learning is often considered as a black box and developers often apply a different pipelines with different parameter settings or models, HORAIZON introduces a novel framework in order to simplify and generalise the approach across multiple tasks. We have developed an efficient system which can be used to analyse all kinds of datasets with different types of machine learning models. Our software framework can be easily used with a generic configuration file, indicating the type of model, data processing, or a learning task to perform.

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MicroDiet application

Microdiet aimed to understand and prevent production of microbially-produced pro-diabetic metabolites in different ethnic group and investigated the impact of (high versus low) dietary changes on human microbiota and glycemic control.