NCT04776070

Establishing Malnutrition Diagnosis System by Using Artificial-intelligence Technology

Establishing Malnutrition Diagnosis System by Using Artificial-intelligence Technology to Improve the Application of Clinical Pathway

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 500 (actual)
• Sponsor: Peking Union Medical College Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 100 Years
• Healthy volunteers: Not accepted

Summary

The prevalence of malnutrition is estimated at 30-50% of hospitalized patients in China. Disease-related malnutrition increases the risk of infection, mortality, length of hospitalization as well as the economic burden. National Nutrition Plan proposed to reduce malnutrition, but a clear, effective roadmap and protocol has not existed yet. Several factors impede to resolve the above challenges. They include :1) the low efficiency of current malnutrition diagnosis methods; 2) the lack of dynamic, standard method that can evaluate nutritional status in quantitative way. To this end, the investigators aim to establish an artificial-intelligence malnutrition diagnosis system to improve the application of malnutrition Clinical Pathway. Firstly, the investigators will establish a multidimensional malnutrition large data set, based on our previously built national hospital nutrition screening data set. It will contain deep 3D facial images, semi-structured and structured electronic medical record. Then, the investigators will use ensemble learning algorithm to establish a fully automatic, artificial-intelligence malnutrition diagnosis model that includes both etiological and phenotypic diagnosis.

Conditions

• Disease-related Malnutrition

Timeline

• Start date: 2021-08-13
• Primary completion: 2022-04-21
• Completion: 2022-05-21
• First posted: 2021-03-01
• Last updated: 2023-03-29

Locations

1 site across 1 country: China