Food, Health, and Data Science

Sciforce
Sciforce
Jun 4 · 4 min read
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Food as Medicine Approach

Amid today’s obsession with mindfulness and body practices, it’s hard not to notice numerous books, documentaries, and podcasts that explore the association between diet and chronic disease or illness, both somatic and mental.

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Anthropometric measurements

Anthropometric measurements are used to assess the size, shape and composition of the human body. Height and weight are used for tracking health conditions, drug dosages, as well as nutritional diseases and energy expenditure. As it is impossible to measure every person, their measurements have to be estimated approximately. In this case, different Machine Learning models, starting from simple linear regressions and going to support vector regression, Gaussian process, and artificial neural networks are used to predict height and weight more accurately.

Biomarkers

Biomarker testing is the core of personalized medicine. In its broadest sense, the term “biomarker” refers to any of the body’s molecules that can be measured to assess health, including molecules from blood, body fluids, and tissue. Biomarker testing looks for molecular signs of health so that doctors can plan the best care. Applying machine learning techniques is critical to assess the importance of different biomarkers and to collect the best marker combinations that have the biggest impact on the person’s response to treatment or — in case of nutrition — to personalize the diet according to the metabolism.

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Nutrigenomics

Nutrigenomics refers to the use of biochemistry, physiology, nutrition, genomics, proteomics, metabolomics, transcriptomics, and epigenomics to seek and explain the reciprocal interactions between genes and nutrients. These interactions are believed to aid the prescription of personalized diets according to one’s genotype mitigating the symptoms of existing diseases or preventing future illnesses, especially in the area of Nontransmissible Chronic Diseases. Data Science is playing a major role in nutrigenomics analysis, as it helps to find patterns predicting future outputs, to study the present status of nutraceuticals in the market, and to control the customers’ responses to them. Using cluster detection, memory-based reasoning, genetic algorithms, link analysis, decision trees, and neural net, huge amounts of data can be handled in a short period of time.

Gut health testing

Gut health tests help to understand what nutrients and toxins are being produced by gut microbiome. Gut contain bacteria, viruses, fungi, phages, yeast, parasites, etc. that may be active to a varying degree and produce nutrients or toxins from the digested food influencing our mood, digestion, immune system, skin, fitness, and many more. Artificial intelligence helps process all information about the gut microbiome to accurately assess risks of development of diseases and to recommend the exact foods you should be eating and foods you should be minimizing with the goal to keep your gut in balance.



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Ukraine-based IT company specialized in development of software solutions based on science-driven information technologies #AI #ML #IoT #NLP #Healthcare #DevOps

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