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 diseases.
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.