Deep Learning using Convolutional LSTM estimates Biological Age from Physical Activity
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Deep Learning using Convolutional LSTM estimates Biological Age from Physical Activity
Authors
Keywords
-
Journal
Scientific Reports
Volume 9, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-08-06
DOI
10.1038/s41598-019-46850-0
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations
- (2018) Polina Mamoshina et al. JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
- Extracting biological age from biomedical data via deep learning: too much of a good thing?
- (2018) Timothy V. Pyrkov et al. Scientific Reports
- Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants
- (2018) Regina Guthold et al. Lancet Global Health
- Artificial intelligence for aging and longevity research: Recent advances and perspectives
- (2018) Alex Zhavoronkov et al. AGEING RESEARCH REVIEWS
- PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging
- (2018) Eugene Bobrov et al. Aging-US
- Demographic Estimation from Face Images: Human vs. Machine Performance
- (2015) Hu Han et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Surface-Based Body Shape Index and Its Relationship with All-Cause Mortality
- (2015) Syed Ashiqur Rahman et al. PLoS One
- Quantification of biological aging in young adults
- (2015) Daniel W. Belsky et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons
- (2014) Krista Fischer et al. PLOS MEDICINE
- DNA methylation age of human tissues and cell types
- (2013) Steve Horvath GENOME BIOLOGY
- Modeling the Rate of Senescence: Can Estimated Biological Age Predict Mortality More Accurately Than Chronological Age?
- (2012) M. E. Levine JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
- A New Body Shape Index Predicts Mortality Hazard Independently of Body Mass Index
- (2012) Nir Y. Krakauer et al. PLoS One
- Informativeness of indices of blood pressure, obesity and serum lipids in relation to ischaemic heart disease mortality: the HUNT-II study
- (2011) Bjørn Mørkedal et al. EUROPEAN JOURNAL OF EPIDEMIOLOGY
- Permutation importance: a corrected feature importance measure
- (2010) André Altmann et al. BIOINFORMATICS
- An empirical comparative study on biological age estimation algorithms with an application of Work Ability Index (WAI)
- (2009) Il Haeng Cho et al. MECHANISMS OF AGEING AND DEVELOPMENT
- Human Age Estimation With Regression on Discriminative Aging Manifold
- (2008) Yun Fu et al. IEEE TRANSACTIONS ON MULTIMEDIA
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started