PGHD-AI Intelligent Model for the Nutritional Assessment and Intervention of Patients After Radical Surgery for Pancreatic Cancer.

Overview

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.

This study is a prospective randomized controlled exploratory clinical trial to recruit 200 patients after radical pancreatic cancer resection. Screening eligible subjects will be randomly assigned to the test group and the control group, and the randomization stratification factors include: age, gender, TNM stage, ECOG score, baseline BMI. The experimental group and the control group received offline routine follow-up combined with PGHD-AI's APP management and routine outpatient follow-up, respectively, to compare the prediction of nutritional status risk and intervention response. The study period is 1 year.

Conditions