Literature DB >> 31352357

Centroid of Age Neighborhoods: A New Approach to Estimate Biological Age.

Syed Ashiqur Rahman, Donald A Adjeroh.   

Abstract

Estimation of human biological age is an important and difficult challenge. Different biomarkers and numerous approaches have been studied for biological age prediction, each with its advantages and limitations. In this paper, we propose a new biological age estimation method, and investigate the performance of the new method. We introduce a centroid based approach, using the notion of age neighborhoods. Specifically, we develop a model, based on which we compute biological age using blood biomarkers, by considering the centroid or mediod of specially selected age neighborhoods. Experiments were performed on the National Health and Human Nutrition Examination Survey dataset with biomarkers (21 451 individuals). Compared with current popular methods for biological age prediction, our experiments show that the proposed age neighborhood model results in an improved performance in human biological age estimation.

Entities:  

Mesh:

Substances:

Year:  2019        PMID: 31352357      PMCID: PMC7362935          DOI: 10.1109/JBHI.2019.2930938

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  17 in total

1.  A new approach to the concept and computation of biological age.

Authors:  Petr Klemera; Stanislav Doubal
Journal:  Mech Ageing Dev       Date:  2005-11-28       Impact factor: 5.432

2.  Automatic age estimation based on facial aging patterns.

Authors:  Xin Geng; Zhi-Hua Zhou; Kate Smith-Miles
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2007-12       Impact factor: 6.226

3.  Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age?

Authors:  Morgan E Levine
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-12-03       Impact factor: 6.053

4.  Demographic Estimation from Face Images: Human vs. Machine Performance.

Authors:  Hu Han; Charles Otto; Xiaoming Liu; Anil K Jain
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2015-06       Impact factor: 6.226

5.  An empirical comparative study on biological age estimation algorithms with an application of Work Ability Index (WAI).

Authors:  Il Haeng Cho; Kyung S Park; Chang Joo Lim
Journal:  Mech Ageing Dev       Date:  2009-12-11       Impact factor: 5.432

6.  Heterogeneity of Human Aging and Its Assessment.

Authors:  Arnold Mitnitski; Susan E Howlett; Kenneth Rockwood
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2017-07-01       Impact factor: 6.053

7.  The Dunedin Multidisciplinary Health and Development Study: overview of the first 40 years, with an eye to the future.

Authors:  Richie Poulton; Terrie E Moffitt; Phil A Silva
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2015-04-03       Impact factor: 4.328

8.  PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging.

Authors:  Eugene Bobrov; Anastasia Georgievskaya; Konstantin Kiselev; Artem Sevastopolsky; Alex Zhavoronkov; Sergey Gurov; Konstantin Rudakov; Maria Del Pilar Bonilla Tobar; Sören Jaspers; Sven Clemann
Journal:  Aging (Albany NY)       Date:  2018-11-09       Impact factor: 5.682

9.  Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality.

Authors:  Syed Ashiqur Rahman; Donald Adjeroh
Journal:  PLoS One       Date:  2015-12-28       Impact factor: 3.240

10.  Extracting biological age from biomedical data via deep learning: too much of a good thing?

Authors:  Timothy V Pyrkov; Konstantin Slipensky; Mikhail Barg; Alexey Kondrashin; Boris Zhurov; Alexander Zenin; Mikhail Pyatnitskiy; Leonid Menshikov; Sergei Markov; Peter O Fedichev
Journal:  Sci Rep       Date:  2018-03-26       Impact factor: 4.379

View more
  1 in total

Review 1.  Deep learning for biological age estimation.

Authors:  Syed Ashiqur Rahman; Peter Giacobbi; Lee Pyles; Charles Mullett; Gianfranco Doretto; Donald A Adjeroh
Journal:  Brief Bioinform       Date:  2021-03-22       Impact factor: 11.622

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.