The Problem of Integrating of Biological and Clinical Markers of Aging

Mitnitski, Arnold; Rockwood, Kenneth

doi:10.1007/978-3-030-24970-0_23

Cited by 8 publications

(9 citation statements)

References 48 publications

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“…The necessary process optimization consists in the ability to obtain a su ciently complete database to describe the aging process, not only qualitatively, but also quantitatively. Another problem lies in the strong difference between biological and clinical markers for assessing human health [Mitnitski A., 2019], however, it can also be solved.…”

Section: Comparison Of Modern and Clinical Methodsmentioning

confidence: 99%

AI, Big Data powered method of life expectancy prediction, severe diseases early stages detection, prevention

Valerievich¹,

Alekseevna²,

Sergeevich³

et al. 2021

Preprint

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Aging is a part of human life, often accompanied by serious illnesses. Nowadays, people sometimes do not live up to the biological aging of the body at all due to late-timed diagnosis of diseases. Unfortunately, the methods of early detection of diseases associated with aging do not yet have the technical equipment that would allow them to be fully implemented. This article provides an overview of methods for defining and analyzing the aging of the body. This is a review article of a novel hardware and software complex for health monitoring developed by a scientific group, which analyzes human bio parameters using artificial intelligence algorithms. The relevance of the proposed system is undeniable due to the used algorithms of artificial intelligence, with the help of which it is possible to quickly and accurately analyze a large amount of data related to human aging. The article will be of interest to developers of artificial intelligence, biostatisticians and scientists working on the definition of aging in the human body.

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Section: Comparison Of Modern and Clinical Methodsmentioning

confidence: 99%

AI, Big Data powered method of life expectancy prediction, severe diseases early stages detection, prevention

Valerievich¹,

Alekseevna²,

Sergeevich³

et al. 2021

Preprint

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“…Необходимая оптимизация процесса заключается в возможности получить достаточно полную базу данных для описания процесса старения не только качественно, но и количественно. Ещё одна проблема заключается в сильном отличии биологических и клинических маркеров оценки здоровья человека [Mitnitski A., 2019], однако и она решаема.…”

Section: сопоставление современных и клинических методовunclassified

Метод Ранней Диагностики Смертельных Заболеваний, Основанный На ИИ И Больших Данных, Способный Значительно Продлить Активную Жизнь

Душкин¹,

Лелекова²,

Максимов³

et al. 2021

Preprint

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В этой статье проводится обзор методик определения и анализа старения организма. Представлен новый разработанный научной группой программно-аппаратный комплекс мониторинга здоровья, который анализирует биопараметры человека с помощью алгоритмов искусственного интеллекта. Актуальность предложенной системы неоспорима в силу использованных алгоритмов искусственного интеллекта, с помощью которых можно быстро и точно проанализировать большое количество данных, касающихся старения человека. Статья будет интересна разработчикам искусственного интеллекта, биостатистикам и учёным, работающим над определением старения человеческого организма.

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“…The global problem of population aging has significantly increased research interest in both the mechanisms of aging and the search for methods for decelerating and reversing aging (Moskalev et al, 2016 , 2017 ; Vaiserman and Lushchak, 2017 ; Krut'ko et al, 2018 ). The fundamental basis of these studies is the methods for quantitative assessment of aging levels both of the body as a whole and of its individual vital organs and systems; in other words, methods for assessing the biological age (BA) of the body as a whole and the partial biological age (BAp) of its vital systems (Dean, 1988 ; Mooradian, 1990 ; Balin, 1996 ; McClean, 1997 ; Anstey and Smith, 1999 ; Krøll and Saxtrup, 2000 ; DeCarlo et al, 2014 ; Negasheva et al, 2014 ; Dontsov and Krut'ko, 2015 ; Moskalev et al, 2016 , 2017 ; Finkel et al, 2017 ; Mitnitski and Rockwood, 2019 ). Moreover, while there are many different methods for BA assessment in literature, there is still no answer to the question: “Which of these methods is the best?” This paper contains an attempt to answer this question.…”

Section: Introductionmentioning

confidence: 99%

Method and Computer System for Dialog Optimization of Aging Biomarker Panels for Biological Age Assessment

et al. 2021

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A concept, method, algorithm, and computer system (CS) of step-by-step dialog optimization of biomarker (BM) panels for assessing human biological age (BA) according to a number of universal criteria based on incomplete and noisy data have been developed. This system provides the ability to automatically build BM panels for BA assessment and to increase the accuracy of BA determination while reducing the number of measured BMs. The optimization criteria are as follows: high correlation of BMs with chronological age (CA); minimum size of BM panels, obtained by rejecting highly cross-correlated BMs; high accuracy of BA assessment; high accuracy of BA/CA dependency interpolation; absence of outliers in BM values, which reduce the BA assessment accuracy; rejection of panels resulting in a high standard deviation for the BA-CA difference; and possible additional criteria entered by the researcher according to the task specifics. The CS input consists of data on physiological, biochemical, and other BMs that change with age. The CS output is a panel of BMs optimized according to the specified optimization criteria. The CS is user-friendly. It allows the user to add optimization criteria that the researcher considers to be important or to remove criteria that the user considers incorrect. The CS may be used in solving practical problems of anti-aging medicine, such as the treatment and prevention of age-related chronic non-infectious diseases representing the main causes of death. The authors' point of view on the role and place of BA diagnostics in this area is discussed.

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The Problem of Integrating of Biological and Clinical Markers of Aging

Cited by 8 publications

References 48 publications

AI, Big Data powered method of life expectancy prediction, severe diseases early stages detection, prevention

AI, Big Data powered method of life expectancy prediction, severe diseases early stages detection, prevention

Метод Ранней Диагностики Смертельных Заболеваний, Основанный На ИИ И Больших Данных, Способный Значительно Продлить Активную Жизнь

Method and Computer System for Dialog Optimization of Aging Biomarker Panels for Biological Age Assessment

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