Deep Personal Multitask Prediction of Diabetes Complication with Attentive Interactions Predicting Diabetes Complications by Multitask-Learning.

ABSTRACT:

Objective

Diabetic complications have brought a tremendous burden for diabetic patients, but the problem of predicting diabetic complications is still unresolved. Our aim is to explore the relationship between hemoglobin A1C (HbA1c), insulin (INS), and glucose (GLU) and diabetic complications in combination with individual factors and to effectively predict multiple complications of diabetes.

Methods

This was a real-world study. Data were collected from 40,913 participants with an average age of 48 years from the Department of Endocrinology of Ruijin Hospital in Shanghai. We proposed deep personal multitask prediction of diabetes complication with attentive interactions (DPMP-DC) to predict the five complication models of diabetes, including diabetic retinopathy, diabetic ne

SUBMITTER: Zuo M 

PROVIDER: S-EPMC9045985 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature