学术报告:AI for Lifestyle self-management: From Food Recognition to Personal Wellness

发布者:发布时间:2019-06-07浏览次数:10

Title:AI for Lifestyle self-management: From Food Recognition to Personal Wellness

Presenters: Dr. Zhaoyan Ming. A senior research scientist in Department of Computer Science and a researcher in Department of Family Medicine National University of Singapore (NUS).

Time:9:30 AM, Monday 10/June/2019.

Place: Room 321, Computer Science and Technology Building, Soochow University

Abstract: The prevalence of chronic diseases such as hyperglycemia, hypertension, and hyperlipidemia (3H) becomes a major concern of public health in many countries, including China. 3H are strongly lifestyle-related and are preventable health problems. Research has shown that self-management support intervention most frequently resulted in significant improvements in patient-level outcomes; nutritional practices alone can reduce the risk of cardiovascular disease by 60%. Unfortunately, efforts to promote sustained healthy eating habits and exercise have been mostly unsuccessful, largely due to the lack of accurate and reliable ways to log an individual’s real-time food intake, and other lifestyle data. We aim to tackle the problem of 3H in the population by leveraging state-of-the-art AI technologies to empower patient self-management and to support primary care practitioners. In the talk, we will focus on the food image recognition technology and the translation into real-world dietary tracking application.To eventually benefit the patients with chronic diseases, obesity, and healthy people with nutrition balancing needs, we are closing the loop with nutrition knowledge and intervention action by the provision of advice, education, and delivery of the food recommendation of a specific diet or tailored meal plan.We are working closely with hospitals, government public health agencies, and end-customers to provide sustainable solutions to promote early diagnosis, treatment, and prevention of chronic into real-world dietary tracking application.To eventually benefit the patients with chronic diseases, obesity, and healthy people with nutrition balancing needs, we are closing the loop with nutrition knowledge and intervention action by the provision of advice, education, and delivery of the food recommendation of a specific diet or tailored meal plan.We are working closely with hospitals, government public health agencies, and end-customers to provide sustainable solutions to promote early diagnosis, treatment, and prevention of chronic into real-world dietary tracking application. To eventually benefit the patients with chronic diseases, obesity, and healthy people with nutrition balancing needs, we are closing the loop with nutrition knowledge and intervention action by the provision of advice, education, and delivery of the food recommendation of a specific diet or tailored meal plan. We are working closely with hospitals, government public health agencies, and end-customers to provide sustainable solutions to promote early diagnosis, treatment, and prevention of chronic diseases. into real-world dietary tracking application.To eventually benefit the patients with chronic diseases, obesity, and healthy people with nutrition balancing needs, we are closing the loop with nutrition knowledge and intervention action by the provision of advice, education, and delivery of the food recommendation of a specific diet or tailored meal plan.We are working closely with hospitals, government public health agencies, and end-customers to provide sustainable solutions to promote early diagnosis, treatment, and prevention of chronic

Introduce: Dr. Zhaoyan Ming. A senior research scientist in Department of Computer Science and a researcher in Department of Family Medicine National University of Singapore (NUS). She is heading the wellness project under NUS-Tsinghua-Southampton Center of Extreme Search and leading the collaboration with the international medical partners in Nutrition Science, Family Medicine, and Tele-medicine.

  

    

  


报告题目:《人工智能用于自我管理的生活方式:从食物识别到个人健康》

报告人:明朝燕博士,新加坡国立大学(NUS)计算机学科学高级研究人员,新加坡国立大学家庭医学系研究员。

报告时间: 2019610号周一,上午930

地点:苏州大学理工楼321

报告摘要:高血糖,高血压,高脂血症(3H)等慢性疾病的流行已经成为中国以及其他国家公共卫生关注的主要问题。3H与生活息息相关,是可以预防的疾病。研究表明,自我管理支持干预体现在患者情况的显著改善; 仅靠营养实践就能将心血管疾病的风险降低60%。不幸的是,推广持续健康的饮食习惯和锻炼的行动大多不成功。主要是因为缺乏准确可靠的方法来记录个人的实时食物摄入量和其他生活方式数据。我们的目标是通过利用最先进的人工智能技术来解决3H患者的人口问题,以增强患者的自我管理能力,并支持初级保健从业者。在本次讲座中,我们将重点介绍食品图像识别技术以及将其转化为现实生活中的饮食跟踪应用。我们正在通过提供建议、教育、提供特定饮食推荐或定制膳食计划,进行营养知识和干预行动,最终使慢性病患者、肥胖患者和需要营养平衡的健康人群受益。我们正与医院、政府公共卫生机构和终端客户密切合作,提供可持续的解决方案,促进慢性病的早期诊断、治疗和预防。

报告人简介:明朝燕博士,新加坡国立大学(NUS)计算机科学系高级研究员,新加坡国立大学家庭医学系研究院。明朝燕博士也是NUS,南安普敦大学和清华大学极限搜索中健康项目的负责人,并负责和营养科学,家庭医学和远程医学等国际医学合作伙伴的合作。