A machine learning approach to predict risk of 30-day readmission: insights from hospital experience surveys completed by patients living with chronic conditions

Kemp Kyle; DSouza Adam; Quan Hude; Santana Maria

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A machine learning approach to predict risk of 30-day readmission: insights from hospital experience surveys completed by patients living with chronic conditions

机译：一种机器学习方法，以预测30天的入住风险：医院体验调查的见解，患有慢性条件的患者完成

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《Quality of life research: An international journal of quality of life aspects of treatment, care and rehabilitation》 |2019年第1期|共1页
作者
Kemp Kyle; DSouza Adam; Quan Hude; Santana Maria;
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作者单位

Univ Calgary Calgary AB Canada;

Univ Calgary Calgary AB Canada;

Univ Calgary Calgary AB Canada;

Univ Calgary Calgary AB Canada;

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原文格式 PDF
正文语种 eng
中图分类医药、卫生;
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1. A machine learning approach to predict risk of 30-day readmission: insights from hospital experience surveys completed by patients living with chronic conditions [J] . Kemp Kyle, DSouza Adam, Quan Hude, Quality of life research: An international journal of quality of life aspects of treatment, care and rehabilitation . 2019,第Suppla1期

机译：一种机器学习方法，以预测30天的入住风险：医院体验调查的见解，患有慢性条件的患者完成
2. The 30-days hospital readmission risk in diabetic patients: predictive modeling with machine learning classifiers [J] . Shang Yujuan, Jiang Kui, Wang Lei, BMC Medical Informatics and Decision Making . 2021,第2期

机译：糖尿病患者的30天医院入院风险：与机器学习分类器预测建模
3. Machine Learning Approach to Predict Risk of 90-Day Hospital Readmissions in Patients With Atrial Fibrillation: Implications for Quality Improvement in Healthcare [J] . Man Hung, Eric S. Hon, Evelyn Lauren, Health Services Research & Managerial Epidemiology . 2020,第a期

机译：预测心房颤动患者90天医院阅览室的机器学习方法：医疗保健质量改善的影响
4. Deep Learning Architectures for Vector Representations of Patients and Exploring Predictors of 30-Day Hospital Readmissions in Patients with Multiple Chronic Conditions [C] . Muhammad Rafiq, George Keel, Pamela Mazzocato, International Workshop on Artificial Intelligence in Health . 2019

机译：用于患者的患者矢量表示的深度学习架构，探讨多元慢性病症患者30天医院阅览室的预测因子
5. Machine Learning Morphisms: A Framework for Designing and Analyzing Machine Learning Work OWs, Applied to Separability, Error Bounds, and 30-Day Hospital Readmissions [D] . ?Cawi, Eric 2021

机译：机器学习态态：设计和分析机器学习工作的框架，适用于可分离性，错误限制和30天医院入院
6. The 30-days hospital readmission risk in diabetic patients: predictive modeling with machine learning classifiers [O] . Yujuan Shang, Kui Jiang, Lei Wang, 2021

机译：糖尿病患者的30天医院入院风险：与机器学习分类器预测建模
7. Machine Learning Approach to Predict Risk of 90-Day Hospital Readmissions in Patients With Atrial Fibrillation: Implications for Quality Improvement in Healthcare [O] . Man Hung, Eric S. Hon, Evelyn Lauren, 2020

机译：机器学习方法预测心房颤动患者90天医院入伍的风险：对医疗保健质量改善的影响

A machine learning approach to predict risk of 30-day readmission: insights from hospital experience surveys completed by patients living with chronic conditions

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