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.

In collaboration with AIBIOMICS BV, we are introducing a new and unique mobile health application that utilizes a novel AI method that is both groundbreaking and convenient. The microbiome of an individual may influence their susceptibility to infectious diseases and contribute to chronic gastrointestinal diseases. We are here to conduct those analyses in a matter of seconds.

The Challenge

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Currently, testing for the gut microbiota includes collecting a portion or all of feces and submitting it to a lab for study. Laboratory examination may involve test-tube tests to identify bacteria that cause infections, similar to how we screen for urinary tract infections in a urine sample. This procedure might take up to a month. The bioinformatic analysis is sophisticated and difficult to comprehend for the average individual.

Additionally, skilled expertise is required for bioinformatics analysis and data visualization. Typically, investigations are performed at a single timepoint, despite the fact that the microbial composition is very dynamic, shifting according to nutrition, circadian rhythm, sampling time of day, and age.

The Solution

The majority of the issues described above, as well as others, are handled by our mobile app. We designed our program in such a way that it can offer users with a rapid and accurate diagnostic using only a picture of their fecal sample. This enables us to provide cost and time effective monitoring of the gut microbiota to our users.

We provide models and tools for automatically analyzing thousands of entire slide images in seconds, as well as for automating the identification of bacteria in the human gut microbiota using machine learning. As with any AI-based system, ours operates on the premise that the more data entered, the more accurate the system becomes. The more photos entered, the more the system can learn, and the more detailed results it will return to patients.

The Results

Group of healthcare workers with digital tablet meeting in hospital boardroom. Medical staff during morning briefing.

This image-based approach has the potential to enable rapid, less-inconvenient, and cost-effective monitoring of the gut microbiota in the future. This may well enable the conduct of multiple tests in a short period of time, providing us with increasingly valuable microbiota time series data, which are currently scarce.There are numerous examples of how this image-based profiling of the human gut microbiota can be used to improve outpatient care performance. For instance, personalized nutrition can be significantly aided by the daily ingestion of microbial changes associated with distinct dietary patterns.