Protocol of a parallel, randomized controlled trial on the effects of a novel personalized nutrition approach by artificial intelligence in real world scenario.

Journal: BMC public health
PMID:

Abstract

BACKGROUND: Nutrition service needs are huge in China. Previous studies indicated that personalized nutrition (PN) interventions were effective. The aim of the present study is to identify the effectiveness and feasibility of a novel PN approach supported by artificial intelligence (AI).

Authors

  • Jingyuan Feng
    School of Public Health, Fudan University, Shanghai, China.
  • Hongwei Liu
    Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia.
  • Shupeng Mai
    Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
  • Jin Su
    Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
  • Jing Sun
    Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Jianjie Zhou
    Basebit (Shanghai) Information Technology Co., Ltd, Shanghai, China.
  • Yingyao Zhang
    Basebit (Shanghai) Information Technology Co., Ltd, Shanghai, China.
  • Yinyi Wang
    Department of Nutrition and Food Science, Education, and Human Development, Steinhardt School of Culture, New York University, New York, USA.
  • Fan Wu
    Department of Product Design, Dalian Polytechnic University, Dalian 116034, China.
  • Guangyong Zheng
    Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China. gyzheng@picb.ac.cn.
  • Zhenni Zhu
    Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China. zhuzhenni@scdc.sh.cn.