Cargando…

Prediction of 30-Day Hospital Readmissions for All-Cause Dental Conditions using Machine Learning

INTRODUCTION: It is unknown whether patients admitted for all-cause dental conditions (ACDC) are at high risk for hospital readmission, or what are the risk factors for dental hospital readmission. OBJECTIVE: We examined the prevalence of, and risk factors associated with, 30-day hospital readmissio...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hung, Man, Li, Wei, Hon, Eric S, Su, Sharon, Su, Weicong, He, Yao, Sheng, Xiaoming, Holubkov, Richard, Lipsky, Martin S
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Dove 2020
Materias:	Original Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549882/ https://www.ncbi.nlm.nih.gov/pubmed/33116985 http://dx.doi.org/10.2147/RMHP.S272824

Ejemplares similares

Predicting all-cause 90-day hospital readmission for dental patients using machine learning methods
por: Li, Wei, et al.
Publicado: (2021)

Using Machine Learning to Predict 30-Day Hospital Readmissions in Patients with Atrial Fibrillation Undergoing Catheter Ablation
por: Hung, Man, et al.
Publicado: (2020)

Machine Learning Approach to Predict Risk of 90-Day Hospital Readmissions in Patients With Atrial Fibrillation: Implications for Quality Improvement in Healthcare
por: Hung, Man, et al.
Publicado: (2020)

Neural networks versus Logistic regression for 30 days all-cause readmission prediction
por: Allam, Ahmed, et al.
Publicado: (2019)

Epidemiology and Predictors of all-cause 30-Day readmission in patients with sickle cell crisis
por: Kumar, Vivek, et al.
Publicado: (2020)

Predicting 30-Day Readmission for Stroke Using Machine Learning Algorithms: A Prospective Cohort Study
por: Chen, Yu-Ching, et al.
Publicado: (2022)

Utilizing electronic health data and machine learning for the prediction of 30-day unplanned readmission or all-cause mortality in heart failure
por: Beecy, Ashley N., et al.
Publicado: (2020)

Machine Learning-Enabled 30-Day Readmission Model for Stroke Patients
por: Darabi, Negar, et al.
Publicado: (2021)

Comparison of predictive modeling approaches for 30-day all-cause non-elective readmission risk
por: Tong, Liping, et al.
Publicado: (2016)

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks
por: Jamei, Mehdi, et al.
Publicado: (2017)

The GeriPACT Initiative to Prevent All-Cause 30-Day Readmission in High Risk Elderly
por: Powers, James S., et al.
Publicado: (2021)

Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital
por: Maali, Yashar, et al.
Publicado: (2018)

Correction: Predicting all-cause risk of 30-day hospital readmission using artificial neural networks
por: Jamei, Mehdi, et al.
Publicado: (2018)

Weak Handgrip at Index Admission for Acute Exacerbation of COPD Predicts All-Cause 30-Day Readmission
por: Witt, Leah J., et al.
Publicado: (2021)

Relationship Between In-Hospital Adverse Events and Hospital Performance on 30-Day All-cause Mortality and Readmission for Patients With Heart Failure
por: Wang, Yun, et al.
Publicado: (2023)

Discharge home health services referral and 30-day all-cause readmission in older adults with heart failure
por: Arundel, Cherinne, et al.
Publicado: (2018)

Machine learning prediction of postoperative unplanned 30-day hospital readmission in older adult
por: Li, Linji, et al.
Publicado: (2022)

B‐Type Natriuretic Peptide Predicts 30‐Day Readmission for Heart Failure but not Readmission for Other Causes
por: Flint, Kelsey M., et al.
Publicado: (2014)

Psychological Stress and 30-Day All-Cause Hospital Readmission in Acute Coronary Syndrome Patients: An Observational Cohort Study
por: Edmondson, Donald, et al.
Publicado: (2014)

A stacking-based model for predicting 30-day all-cause hospital readmissions of patients with acute myocardial infarction
por: Zhang, Zhen, et al.
Publicado: (2020)

Risk stratification with explainable machine learning for 30-day procedure-related mortality and 30-day unplanned readmission in patients with peripheral arterial disease
por: Cox, Meredith, et al.
Publicado: (2022)

The 30-days hospital readmission risk in diabetic patients: predictive modeling with machine learning classifiers
por: Shang, Yujuan, et al.
Publicado: (2021)

Prediction of 30-Day Readmission After Stroke Using Machine Learning and Natural Language Processing
por: Lineback, Christina M., et al.
Publicado: (2021)

Evaluating machine learning algorithms to Predict 30-day Unplanned REadmission (PURE) in Urology patients
por: Welvaars, Koen, et al.
Publicado: (2023)

High Mortality among 30-Day Readmission after Stroke: Predictors and Etiologies of Readmission
por: Nouh, Amre M., et al.
Publicado: (2017)

Head and neck cancer readmission reduction (HANCARRE) project: Reducing 30‐day readmissions
por: Yang, Sara, et al.
Publicado: (2022)

Clinical Preventability of 30‐Day Readmission After Percutaneous Coronary Intervention
por: Wasfy, Jason H., et al.
Publicado: (2014)

Machine learning methods to predict 30-day hospital readmission outcome among US adults with pneumonia: analysis of the national readmission database
por: Huang, Yinan, et al.
Publicado: (2022)

Risk factors associated with 30‐day all‐cause unplanned hospital readmissions at a tertiary children's hospital in Western Australia
por: Zhou, Huaqiong, et al.
Publicado: (2019)

888. Impact of Mandatory Infectious Diseases Consult on All-cause In-patient Mortality and 30-Day Readmission in Patients with Severe Sepsis
por: Hou, Cindy, et al.
Publicado: (2019)

Comparison of Back-Propagation Neural Network, LACE Index and HOSPITAL Score in Predicting All-Cause Risk of 30-Day Readmission
por: Lin, Chaohsin, et al.
Publicado: (2021)

Prognostic value of patient‐reported outcomes in predicting 30 day all‐cause readmission among older patients with heart failure
por: Zhang, Xiaonan, et al.
Publicado: (2022)

Readmission After COPD Exacerbation Scale: determining 30-day readmission risk for COPD patients
por: Lau, Christine SM, et al.
Publicado: (2017)

“Weekend Effect” on 30-Day Readmissions among Stroke Survivors: An Analysis of the National Readmission Database
por: Khaksari, Bijan J., et al.
Publicado: (2019)

Examining 30-day COPD readmissions through the emergency department
por: Rezaee, Michael E, et al.
Publicado: (2017)

Paracentesis in cirrhotics is associated with increased risk of 30-day readmission
por: Sobotka, Lindsay A, et al.
Publicado: (2018)

The Impact of Ischaemic Stroke Subtype on 30-day Hospital Readmissions
por: Bjerkreim, Anna Therese, et al.
Publicado: (2018)

Patient vs provider perspectives of 30-day hospital readmissions
por: Smeraglio, Andrea, et al.
Publicado: (2019)

The relationship between diabetes mellitus and 30-day readmission rates
por: Ostling, Stephanie, et al.
Publicado: (2017)

Medication adherence as a predictor of 30-day hospital readmissions
por: Rosen, Olga Z, et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_cv3kjper3654l19n14i6jlq0js