This multidimensional analysis of the impact of artificial intelligence on the future of medicine aims to give some clues on foreseen categories of applications as well as their societal implications in terms of risks...This multidimensional analysis of the impact of artificial intelligence on the future of medicine aims to give some clues on foreseen categories of applications as well as their societal implications in terms of risks/benefits.Artificial intelligence encompasses technologies recapitulating four dimensions of human intelligence,i.e.sensing,thinking,acting and learning.Intelligent machines are converging with advancing biotechnologies to shape the future of medicine,in synergy with continuous progress in our understanding of system biology,brain physiology,biology of aging,computational sciences and decision-making theories.Data-driven predictive models of health-related problems can be generated to inform decisions and actions,allowing to enhance productivity in new drug development,increase the cost-effectiveness of fully integrated health care systems and empower patients and healthy individuals to better manage their disease or their health,respectively.Consequently,the future will likely take the form of a computational precision medicine continuously informed by data capture and modeling to propose preventive measures or therapies precisely tailored to characteristics of each individual.展开更多
文摘This multidimensional analysis of the impact of artificial intelligence on the future of medicine aims to give some clues on foreseen categories of applications as well as their societal implications in terms of risks/benefits.Artificial intelligence encompasses technologies recapitulating four dimensions of human intelligence,i.e.sensing,thinking,acting and learning.Intelligent machines are converging with advancing biotechnologies to shape the future of medicine,in synergy with continuous progress in our understanding of system biology,brain physiology,biology of aging,computational sciences and decision-making theories.Data-driven predictive models of health-related problems can be generated to inform decisions and actions,allowing to enhance productivity in new drug development,increase the cost-effectiveness of fully integrated health care systems and empower patients and healthy individuals to better manage their disease or their health,respectively.Consequently,the future will likely take the form of a computational precision medicine continuously informed by data capture and modeling to propose preventive measures or therapies precisely tailored to characteristics of each individual.
