The future of healthy ageing: the role of big data and artificial intelligence in improving health through better disease prevention, diagnosis, and profiling
摘要截稿:
全文截稿: 2024-08-15
影响因子: 3.63
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 医学 - 3区
• 小类 : 妇产科学 - 3区
Overview
With the continuing increase in life expectancy and an ageing population globally, monitoring health and disease risk factors over the life course has been rising to the forefront of investments in technological developments and artificial intelligence. These developments are promising for understanding behavioral and physiological factors in disease diagnosis and treatment optimization as well as disease prevention and public health strategies. Over the past two decades, there has been an explosion of tools such as wearable devices and novel metabolomic biomarkers that can yield precise parameters of lifestyle and physiological factors. Due to artificial intelligence and machine learning tools, integrating big data with biomedical and genetic markers of ageing and disease has proved possible. However, the technological implementation in clinical and public health practice remains erratic for reasons of capacity, ethics, cost-effectiveness, standardization and lack of education of both health providers and the general public. There is an encouraging amount of the evidence regarding the validity of such tools and how machine learning could help improve disease diagnosis and patient care as well as disease prevention and interventions for the population healthy ageing.The aim of this special issue is to cast new light over the existing evidence and recent developments that investigate in tandem the use of technological devices in understanding and monitoring parameters of behaviour and ageing to improve diagnostics and prevention. These include original, validation, opinion, and systematic/scoping review and meta-analyses studies across multiple disciplines in behavioural science, medical diagnostics, cost-effectiveness, and public health. We welcome papers that tackle the use of smart devices, big data, and wearables from provider, user, researcher, medical, and regulator ends for a multitude of parameters relating to healthy ageing. These parameters of ageing could include: 1) physiological parameters such as heart rate, heart rate variability, heart rate recovery, gait, VO2 Max, glucose dynamics, and blood pressure 2) movement-related daily activities and positions such as sleep, physical activity, sedentary behaviour, energy expenditure, walking speed, and 3) biomarkers, domains, and metabolomics of ageing such as immune, cardiovascular, and lung functions, microbiome, pain, cognition, physical function, and quality of life, and 4) user experience.
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Guest editors:
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Marilyne Menassa, PhDUniversity Medical Centre Utrecht, Utrecht, NetherlandsOscar H. Franco, MD, PhDUniversity Medical Centre Utrecht, Utrecht, Netherlands