High-performance medicine: the convergence of human and artificial intelligence
EJ Topol - Nature medicine, 2019 - nature.com
The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …
enabled by the use of labeled big data, along with markedly enhanced computing power …
Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
Objective To conduct a systematic review of deep learning models for electronic health
record (EHR) data, and illustrate various deep learning architectures for analyzing different …
record (EHR) data, and illustrate various deep learning architectures for analyzing different …
[HTML][HTML] Artificial intelligence for aging and longevity research: Recent advances and perspectives
A Zhavoronkov, P Mamoshina, Q Vanhaelen… - Ageing research …, 2019 - Elsevier
The applications of modern artificial intelligence (AI) algorithms within the field of aging
research offer tremendous opportunities. Aging is an almost universal unifying feature …
research offer tremendous opportunities. Aging is an almost universal unifying feature …
Extracting biological age from biomedical data via deep learning: too much of a good thing?
TV Pyrkov, K Slipensky, M Barg, A Kondrashin… - Scientific reports, 2018 - nature.com
Age-related physiological changes in humans are linearly associated with age. Naturally,
linear combinations of physiological measures trained to estimate chronological age have …
linear combinations of physiological measures trained to estimate chronological age have …
[HTML][HTML] Estimating age and gender from electrocardiogram signals: A comprehensive review of the past decade
Twelve lead electrocardiogram signals capture unique fingerprints about the body's
biological processes and electrical activity of heart muscles. Machine learning and deep …
biological processes and electrical activity of heart muscles. Machine learning and deep …
Predicting opioid dependence from electronic health records with machine learning
Background The opioid epidemic in the United States is averaging over 100 deaths per day
due to overdose. The effectiveness of opioids as pain treatments, and the drug-seeking …
due to overdose. The effectiveness of opioids as pain treatments, and the drug-seeking …
Multi-omic biological age estimation and its correlation with wellness and disease phenotypes: a longitudinal study of 3,558 individuals
Biological age (BA), derived from molecular and physiological measurements, has been
proposed to better predict mortality and disease than chronological age (CA). In the present …
proposed to better predict mortality and disease than chronological age (CA). In the present …
Deep learning for biological age estimation
S Ashiqur Rahman, P Giacobbi, L Pyles… - Briefings in …, 2021 - academic.oup.com
Modern machine learning techniques (such as deep learning) offer immense opportunities
in the field of human biological aging research. Aging is a complex process, experienced by …
in the field of human biological aging research. Aging is a complex process, experienced by …
Computational methods for single-cell imaging and omics data integration
Integrating single cell omics and single cell imaging allows for a more effective
characterisation of the underlying mechanisms that drive a phenotype at the tissue level …
characterisation of the underlying mechanisms that drive a phenotype at the tissue level …
Towards Pharma 4.0 in clinical trials: A future-orientated perspective
Abstract Pharma 4.0, a technology ecosystem in drug development analogous to Industry
4.0 in healthcare, is transforming the traditional approach to drug discovery and …
4.0 in healthcare, is transforming the traditional approach to drug discovery and …