Cargando…

Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning

OBJECTIVE: Liver cirrhosis is a leading cause of death and effects millions of people in the United States. Early mortality prediction among patients with cirrhosis might give healthcare providers more opportunity to effectively treat the condition. We hypothesized that laboratory test results and o...

Descripción completa

Detalles Bibliográficos
Autores principales:	Guo, Aixia, Mazumder, Nikhilesh R., Ladner, Daniela P., Foraker, Randi E.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2021
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407576/ https://www.ncbi.nlm.nih.gov/pubmed/34464403 http://dx.doi.org/10.1371/journal.pone.0256428

Ejemplares similares

Application of a time-series deep learning model to predict cardiac dysrhythmias in electronic health records
por: Guo, Aixia, et al.
Publicado: (2021)

Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models
por: Guo, Aixia, et al.
Publicado: (2021)

Development and Structure of an Accurate Machine Learning Algorithm to Predict Inpatient Mortality and Hospice Outcomes in the Coronavirus Disease 2019 Era
por: Chi, Stephen, et al.
Publicado: (2022)

Discovering disease–disease associations using electronic health records in The Guideline Advantage (TGA) dataset
por: Guo, Aixia, et al.
Publicado: (2021)

The National COVID Cohort Collaborative: Analyses of Original and Computationally Derived Electronic Health Record Data
por: Foraker, Randi, et al.
Publicado: (2021)

The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation
por: Guo, Aixia, et al.
Publicado: (2020)

The answer at our fingertips: Volume status in cirrhosis determined by machine learning and pulse oximeter waveform
por: Mazumder, Nikhilesh R., et al.
Publicado: (2022)

Coronary heart disease and mortality following a breast cancer diagnosis
por: Guo, Aixia, et al.
Publicado: (2020)

Using Artificial Intelligence to Predict Cirrhosis From Computed Tomography Scans
por: Mazumder, Nikhilesh R., et al.
Publicado: (2023)

Community-level determinants of obesity: harnessing the power of electronic health records for retrospective data analysis
por: Roth, Caryn, et al.
Publicado: (2014)

Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach
por: Vaid, Akhil, et al.
Publicado: (2021)

Portal Venous Remodeling Determines the Pattern of Cirrhosis Decompensation: A Systems Analysis
por: Mazumder, Nikhilesh R., et al.
Publicado: (2023)

Development, Validation, and Evaluation of a Simple Machine Learning Model to Predict Cirrhosis Mortality
por: Kanwal, Fasiha, et al.
Publicado: (2020)

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

Cardiovascular Health Trends in Electronic Health Record Data (2012–2015): A Cross-Sectional Analysis of The Guideline Advantage™
por: Rudy, Joyce E., et al.
Publicado: (2019)

Predicting opioid dependence from electronic health records with machine learning
por: Ellis, Randall J., et al.
Publicado: (2019)

Predicting the Mortality and Readmission of In-Hospital Cardiac Arrest Patients With Electronic Health Records: A Machine Learning Approach
por: Chi, Chien-Yu, et al.
Publicado: (2021)

Mortality prediction of patients in intensive care units using machine learning algorithms based on electronic health records
por: Choi, Min Hyuk, et al.
Publicado: (2022)

ML2 Supervised Machine Learning Predicts Mortality in COVID-19 Patients Using Electronic Health Records
por: Marinaro, X., et al.
Publicado: (2021)

Electronic health record data quality assessment and tools: a systematic review
por: Lewis, Abigail E, et al.
Publicado: (2023)

Advanced Care Planning for Hospitalized Patients Following Clinician Notification of Patient Mortality by a Machine Learning Algorithm
por: Chi, Stephen, et al.
Publicado: (2023)

Machine learning for suicide risk prediction in children and adolescents with electronic health records
por: Su, Chang, et al.
Publicado: (2020)

Predicting Cardiovascular Disease in Psychiatric Patients: Machine Learning with Electronic Health Records
por: Bernstorff, M., et al.
Publicado: (2022)

Active Use of Electronic Health Records (EHRs) and Personal Health Records (PHRs) for Epidemiologic Research: Sample Representativeness and Nonresponse Bias in a Study of Women During Pregnancy
por: Bower, Julie K, et al.
Publicado: (2017)

Amiodarone-Induced Cirrhosis of Liver: What Predicts Mortality?
por: Hussain, Nasir, et al.
Publicado: (2013)

Machine learning-based model for predicting the esophagogastric variceal bleeding risk in liver cirrhosis patients
por: Hou, Yixin, et al.
Publicado: (2023)

Women and ethnoracial minorities with poor cardiovascular health measures associated with a higher risk of developing mood disorder
por: Guo, Aixia, et al.
Publicado: (2021)

Using Machine Learning and the Electronic Health Record to Predict Complicated Clostridium difficile Infection
por: Li, Benjamin Y, et al.
Publicado: (2019)

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters
por: Esteban-Escaño, Javier, et al.
Publicado: (2021)

Machine Learning-Based Prediction Model of Preterm Birth Using Electronic Health Record
por: Sun, Qi, et al.
Publicado: (2022)

Machine learning model to predict mental health crises from electronic health records
por: Garriga, Roger, et al.
Publicado: (2022)

Benchmarking emergency department prediction models with machine learning and public electronic health records
por: Xie, Feng, et al.
Publicado: (2022)

EXPLAINABLE MACHINE-LEARNING FOR PREDICTING PREOPERATIVE FRAILTY PHENOTYPE USING ELECTRONIC HEALTH RECORDS
por: Mardini, Mamoun, et al.
Publicado: (2022)

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage
por: Guo, Aixia, et al.
Publicado: (2020)

Factors Predicting Mortality of Acute Variceal Bleeding in Liver Cirrhosis
por: Mandal, Amrendra Kumar, et al.
Publicado: (2018)

Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease
por: Steele, Andrew J., et al.
Publicado: (2018)

Development of Machine Learning Algorithms Incorporating Electronic Health Record Data, Patient-Reported Outcomes, or Both to Predict Mortality for Outpatients With Cancer
por: Parikh, Ravi B., et al.
Publicado: (2022)

Machine learning using institution-specific multi-modal electronic health records improves mortality risk prediction for cardiac surgery patients
por: Weiss, Aaron J., et al.
Publicado: (2023)

Subphenotyping depression using machine learning and electronic health records
por: Xu, Zhenxing, et al.
Publicado: (2020)

Learning Models for Traumatic Brain Injury Mortality Prediction on Pediatric Electronic Health Records
por: Fonseca, João, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_u2sg3851mj68valm71tgsj1p6o