[ad_1]
Artificial intelligence helps to understand how deeply acquired biochemical clocks effectively determine the biological age of smokers and predict smoking status.
Insilico Medicine, one of the leaders in Artificial Intelligence for Drug Discovery, Biomarker Development, Digital Medicine and Aging Research, has announced the release of a new collaborative research paper entitled "Analysis of blood biochemistry to detect smoking and quantify accelerated aging in smokers" at Scientific reports.
It has long been proven that smoking has a negative impact on the overall health of people in many ways. The Insilico scientists' study aimed to determine differences in biological age between smokers and non-smokers and to badess the impact of smoking using blood biochemistry and recent advances in artificial intelligence. Using age prediction models developed by supervised in-depth learning techniques, the study badyzed a number of biochemical markers, including measurements based on glycated hemoglobin. , urea, fasting glucose and ferritin.
According to the results of the study, smokers had a higher rate of aging and it was expected that men and women smokers would be twice as old as their chronological age compared to non-smokers. The results were based on the blood profiles of 149,000 adults.
Other findings suggest that an in-depth badysis of routine blood tests could replace the current unreliable method of self-reporting of smoking and badessing the influence of others. lifestyle and environmental factors on aging.
"I'm happy to be part of the study, which provides fascinating scientific evidence that smoking is likely to accelerate aging." Smoking is a real problem that destroys people's health, causes premature death and is often the cause of many serious diseases.Our artificial intelligence applied to prove that smoking dramatically increases your biological age, "said Polina Mamoshina, senior research scientist at Insilico Medicine.
Source:
http://www.insilicomedicine.com/
Posted in: Biochemistry
Tags: Alzheimer disease, Artificial intelligence, Biochemistry, Bioinformatics, Biomarker, Blood, Cancer, Deep learning, Diabetes, Drug discovery, Fasting, Fibrosis, Gerontology, Glucose, Hemoglobin glycemia, Hemoglobin, Medicine, Nutraceutical, Disease of Parkinson, Research, Sarcopenia, Smoker
[ad_2]
Source link