Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up

Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up

Background: Some patients with acromegaly do not reach the remission standard in the short term after surgery but achieve remission without additional postoperative treatment during long-term follow-up; this phenomenon is defined as postoperative delayed remission (DR). DR may complicate the interpr...

Full description

Bibliographic Details
Main Authors: Congxin Dai, Yanghua Fan, Yichao Li, Xinjie Bao, Yansheng Li, Mingliang Su, Yong Yao, Kan Deng, Bing Xing, Feng Feng, Ming Feng, Renzhi Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Endocrinology
Subjects:
acromegaly
delayed remission
machine learning
LIME
SHAP
Online Access:https://www.frontiersin.org/article/10.3389/fendo.2020.00643/full

Internet

https://www.frontiersin.org/article/10.3389/fendo.2020.00643/full

Similar Items