How AI and Aging Research can help life insurance companies?
Recent advances in artificial intelligence and machine learning, combined with increased computational power, has led to an increase in interest in longevity biotechnology (30114-2). This hype is being used by hundreds of data scientists, companies and researchers to drive research and discover new technologies for aging research.
Biomarkers of ageing are a major area of research in aging. They can give a true biological age to humans, which may differ from their chronological age. Deep aging clocks are one of the most advanced biomarkers for aging. They can be used to predict both biological age and mortality in humans. Steven Horvath, in 2013, published an article entitled ‘DNA Methylation Age of Human Tissues and Cell Types’. In this article he described the development of a multiple-tissue age predictor that can be used to estimate the DNA methylation ages of most human tissues and cells. He created an aging clock which can be used in research on developmental biology, cancer and aging.
Since 2013, there have been many more studies about such clocks. In 2016, I was part a team that published a paper on the first deep clock, titled \”Deep Biomarkers of Human Aging: Application of Deep Neural Networks to Biomarker Development.\” Since then, other aging timers have been developed which can predict mortality as well as age. It is evident that the longevity biotechnology sector is growing and there will be a lot of progress in the aging research in the coming years. AI-based aging watches are a great way for insurance companies to enter the aging research field and make a real contribution while protecting their businesses and innovating.
Source:
https://www.forbes.com/sites/alexzhavoronkov/2022/02/09/how-ai-and-aging-research-can-help-life-insurance-companies/?sh=4e2326204523
