主题：AI and the future of health and aging
时间：2024年11月12日13：30-15：00
地点：2教228
报告人简介：
Juan Mantilla 教授
Juan Mantilla is a computer scientist whose work is dedicated to advancing proactive healthcare through technology. Originally from Venezuela, Juan’s early fascination with data’s potential led him to pursue a Ph.D. in Signal Processing in France, where he specialized in developing algorithms to enhance medical diagnostics. Now serving as Director of R&D at IDP Santé, he leads the development of SMARTPREDICT, a groundbreaking AI tool designed to detect early indicators of health decline, enabling timely, preventive interventions. SMARTPREDICT’s applications range from monitoring changes in body composition to assessing fall risk in elderly patients, supporting healthcare providers in promoting independence and health longevity. Juan’s work reflects his commitment to blending scientific rigor with practical healthcare solutions, demonstrating that innovation in technology can play a vital role in improving quality of life and empowering individuals to age with strength and dignity.
报告题目：Revolutionizing Health Prevention with SMART PREDICT – How AI is changing the future of health and aging
摘要：In this talk, I will present SMARTPREDICT, an innovative tool developed by IDP Santé to address the growing challenge of early frailty detection. Frailty is a significant public health concern, particularly in aging populations, as it increases the risk of falls, hospitalization, and diminished quality of life. SMARTPREDICT leverages advanced technology to offer healthcare professionals a comprehensive, efficient solution for early intervention. I will first provide an overview of IDP Santé’s mission and the development journey of SMARTPREDICT. This device is designed to deliver a rapid and detailed assessment of patients’ health status by analyzing mobility, balance, muscle mass, and psychological well-being. Next, I will discuss the scientific principles behind SMARTPREDICT, including the integration of machine learning and data analytics. Key features such as Center of Pressure (COP) analysis and personalized health tracking will be highlighted to illustrate its capabilities. Then, I will present real-world examples where SMARTPREDICT has been successfully implemented. Finally, I will outline the future roadmap for SMARTPREDICT, including upcoming features like emotional health assessments and expanded diagnostics for chronic conditions. I will also discuss potential collaboration opportunities, particularly in validating the tool within different healthcare systems, such as in China.