Evaluation of a Combined PGHD-AI Intelligent Model for the Nutritional Assessment and Intervention of Patients After Radical Surgery for Pancreatic Cancer.
This study will collect patient PRO (physical strength, pain, defecation, appetite, weight, etc.) data through the APP, use corpus collection cards, facial photography and other technologies to collect PGHD characteristic phenotypes, and then combine artificial intelligence technology to train and cultivate agents (agents) to carry out joint offline routine follow-up of patients after radical pancreatic cancer resection to evaluate the feasibility of nutritional risk assessment intervention. Thus, the feasibility of artificial intelligence prediction of health status is verified, and an efficient follow-up tool and nutritional support evaluation plan are provided for the management of pancreatic cancer patients throughout the course of the disease, so as to improve the treatment prognosis and quality of life of pancreatic cancer patients.
• Age: 18-80 years old, and voluntarily signed the informed consent form to participate in the study;
• Meet the clinical and pathological diagnostic criteria for pancreatic cancer (ICD-10:C25);
• After radical surgery, fully recovered from surgery at randomization;
• ECOG PS score 0-1 ;
• Have objective conditions to complete follow-up and examination during the study process.