Cargando…

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated encephalopathy

OBJECTIVE: Our study aimed to identify predictors as well as develop machine learning (ML) models to predict the risk of 30-day mortality in patients with sepsis-associated encephalopathy (SAE). MATERIALS AND METHODS: ML models were developed and validated based on a public database named Medical In...

Descripción completa

Detalles Bibliográficos
Autores principales:	Peng, Liwei, Peng, Chi, Yang, Fan, Wang, Jian, Zuo, Wei, Cheng, Chao, Mao, Zilong, Jin, Zhichao, Li, Weixin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2022
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252033/ https://www.ncbi.nlm.nih.gov/pubmed/35787248 http://dx.doi.org/10.1186/s12874-022-01664-z

Ejemplares similares

A Machine Learning Approach for the Prediction of Traumatic Brain Injury Induced Coagulopathy
por: Yang, Fan, et al.
Publicado: (2021)

Using machine learning methods to predict 28-day mortality in patients with hepatic encephalopathy
por: Zhang, Zhe, et al.
Publicado: (2023)

Development of a nomogram to predict 30-day mortality of patients with sepsis-associated encephalopathy: a retrospective cohort study
por: Yang, Yang, et al.
Publicado: (2020)

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost
por: Hou, Nianzong, et al.
Publicado: (2020)

Machine Learning Models to Predict 30-Day Mortality in Mechanically Ventilated Patients
por: Kim, Jong Ho, et al.
Publicado: (2021)

An administrative model for benchmarking hospitals on their 30-day sepsis mortality
por: Darby, Jennifer L., et al.
Publicado: (2019)

Higher glycemic variability within the first day of ICU admission is associated with increased 30-day mortality in ICU patients with sepsis
por: Chao, Wen-Cheng, et al.
Publicado: (2020)

Group‐based trajectory modeling of intracranial pressure in patients with acute brain injury: Results from multi‐center ICUs, 2008–2019
por: Yang, Fan, et al.
Publicado: (2022)

Automated Machine Learning in Predicting 30-Day Mortality in Patients with Non-Cholestatic Cirrhosis
por: Yu, Chenyan, et al.
Publicado: (2022)

Sentiment Analysis for Necessary Preview of 30-Day Mortality in Sepsis Patients and the Control Strategies
por: Zou, Yanqun, et al.
Publicado: (2021)

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)

Explainable ensemble machine learning model for prediction of 28-day mortality risk in patients with sepsis-associated acute kidney injury
por: Yang, Jijun, et al.
Publicado: (2023)

Association between early serum cholinesterase activity and 30-day mortality in sepsis-3 patients: A retrospective cohort study
por: Peng, Zheng-Liang, et al.
Publicado: (2018)

A Machine Learning-Based Prediction of Hospital Mortality in Patients With Postoperative Sepsis
por: Yao, Ren-qi, et al.
Publicado: (2020)

Predicting 30-day mortality of patients with pneumonia in an emergency department setting using machine-learning models
por: Kang, Soo Yeon, et al.
Publicado: (2020)

A Predictive Model for 30-Day Mortality of Fungemia in ICUs
por: Xie, Peng, et al.
Publicado: (2022)

Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning
por: Lu, Xiao, et al.
Publicado: (2022)

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

A prediction model for 30-day mortality of sepsis patients based on intravenous fluids and electrolytes
por: Wang, Yan, et al.
Publicado: (2022)

Early predicting 30-day mortality in sepsis in MIMIC-III by an artificial neural networks model
por: Su, Yingjie, et al.
Publicado: (2022)

Early Prediction of Mortality, Severity, and Length of Stay in the Intensive Care Unit of Sepsis Patients Based on Sepsis 3.0 by Machine Learning Models
por: Su, Longxiang, et al.
Publicado: (2021)

Neutrophil-to-lymphocyte ratio predicts 30-, 90-, and 180-day readmissions of patients with hepatic encephalopathy
por: Zhang, Lin, et al.
Publicado: (2023)

30 days mortality prediction and risk factor analysis of Asian patients with ACS using interpretable machine learning algorithm
por: Kasim, S, et al.
Publicado: (2022)

Mechanical Learning for Prediction of Sepsis-Associated Encephalopathy
por: Zhao, Lina, et al.
Publicado: (2021)

Machine Learning Methods for Predicting Long-Term Mortality in Patients After Cardiac Surgery
por: Yu, Yue, et al.
Publicado: (2022)

30 Days Mortality Prognostic Value of POCT Bio-Adrenomedullin and Proenkephalin in Patients with Sepsis in the Emergency Department
por: Casalboni, Silvia, et al.
Publicado: (2022)

Association between ICU admission (neutrophil + monocyte)/lymphocyte ratio and 30-day mortality in patients with sepsis: a retrospective cohort study
por: Guo, Manliang, et al.
Publicado: (2023)

Alcohol Abuse Associated With Increased Risk of Angiographic Vasospasm and Delayed Cerebral Ischemia in Patients With Aneurysmal Subarachnoid Hemorrhage Requiring Mechanical Ventilation
por: Zhao, Lei, et al.
Publicado: (2022)

Review of Neurofilaments as Biomarkers in Sepsis-Associated Encephalopathy
por: Zhang, Qiulei, et al.
Publicado: (2023)

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)

Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study
por: Wang, Wenjuan, et al.
Publicado: (2022)

Prediction of 30-day mortality in heart failure patients with hypoxic hepatitis: Development and external validation of an interpretable machine learning model
por: Sun, Run, et al.
Publicado: (2022)

An immune-related gene signature predicts the 28-day mortality in patients with sepsis
por: Peng, Yaojun, et al.
Publicado: (2023)

Association between different MAP levels and 30-day mortality in sepsis patients: a propensity-score-matched, retrospective cohort study
por: Zhong, Xiaoxin, et al.
Publicado: (2023)

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

The association between autoimmune disease and 30-day mortality among sepsis ICU patients: a cohort study
por: Sheth, Mallory, et al.
Publicado: (2019)

30-Day Mortality Following Palliative Radiotherapy
por: Vázquez, Miriam, et al.
Publicado: (2021)

Correction: Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study
por: Wang, Wenjuan, et al.
Publicado: (2022)

Sepsis-Associated Encephalopathy
por: Cotena, Simona, et al.
Publicado: (2012)

Sepsis Associated Encephalopathy
por: Chaudhry, Neera, et al.
Publicado: (2014)

Cannot write session to /tmp/vufind_sessions/sess_8dg5qtv91mjsf224ndsolab88l