Cargando…

Prediction of Acute Kidney Injury With a Machine Learning Algorithm Using Electronic Health Record Data

BACKGROUND: A major problem in treating acute kidney injury (AKI) is that clinical criteria for recognition are markers of established kidney damage or impaired function; treatment before such damage manifests is desirable. Clinicians could intervene during what may be a crucial stage for preventing...

Descripción completa

Detalles Bibliográficos
Autores principales:	Mohamadlou, Hamid, Lynn-Palevsky, Anna, Barton, Christopher, Chettipally, Uli, Shieh, Lisa, Calvert, Jacob, Saber, Nicholas R., Das, Ritankar
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	SAGE Publications 2018
Materias:	Original Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080076/ https://www.ncbi.nlm.nih.gov/pubmed/30094049 http://dx.doi.org/10.1177/2054358118776326

Ejemplares similares

Using electronic health record collected clinical variables to predict medical intensive care unit mortality
por: Calvert, Jacob, et al.
Publicado: (2016)

High-performance detection and early prediction of septic shock for alcohol-use disorder patients
por: Calvert, Jacob, et al.
Publicado: (2016)

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach
por: Desautels, Thomas, et al.
Publicado: (2016)

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU
por: Mao, Qingqing, et al.
Publicado: (2018)

Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients
por: Calvert, Jacob, et al.
Publicado: (2019)

Using Transfer Learning for Improved Mortality Prediction in a Data-Scarce Hospital Setting
por: Desautels, Thomas, et al.
Publicado: (2017)

Predicting pulmonary embolism among hospitalized patients with machine learning algorithms
por: Ryan, Logan, et al.
Publicado: (2022)

Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury Prediction
por: Le, Sidney, et al.
Publicado: (2021)

Pediatric Severe Sepsis Prediction Using Machine Learning
por: Le, Sidney, et al.
Publicado: (2019)

Prediction of short-term mortality in acute heart failure patients using minimal electronic health record data
por: Radhachandran, Ashwath, et al.
Publicado: (2021)

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm
por: Maharjan, Jenish, et al.
Publicado: (2022)

Prediction of diabetic kidney disease with machine learning algorithms, upon the initial diagnosis of type 2 diabetes mellitus
por: Allen, Angier, et al.
Publicado: (2022)

A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study
por: Allen, Angier, et al.
Publicado: (2020)

Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial
por: Shimabukuro, David W, et al.
Publicado: (2017)

Use of an Electronic Medical Record “Dotphrase” Data Template for a Prospective Head Injury Study
por: Offerman, Steven R., et al.
Publicado: (2013)

Predicting ventilator-associated pneumonia with machine learning
por: Giang, Christine, et al.
Publicado: (2021)

Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach
por: Desautels, Thomas, et al.
Publicado: (2017)

Machine learning to predict progression of non‐alcoholic fatty liver to non‐alcoholic steatohepatitis or fibrosis
por: Ghandian, Sina, et al.
Publicado: (2022)

Maximizing Kolmogorov Complexity for accurate and robust bright field cell segmentation
por: Mohamadlou, Hamid, et al.
Publicado: (2014)

Predicting Falls in Long-term Care Facilities: Machine Learning Study
por: Thapa, Rahul, et al.
Publicado: (2022)

A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients
por: Ryan, Logan, et al.
Publicado: (2021)

Personalized stratification of hospitalization risk amidst COVID-19: A machine learning approach
por: Lam, Carson, et al.
Publicado: (2021)

Machine learning landscapes and predictions for patient outcomes
por: Das, Ritankar, et al.
Publicado: (2017)

Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratification
por: Panchavati, Saarang, et al.
Publicado: (2021)

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

Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals
por: Burdick, Hoyt, et al.
Publicado: (2020)

Machine Learning Prediction of Hypoglycemia and Hyperglycemia From Electronic Health Records: Algorithm Development and Validation
por: Witte, Harald, et al.
Publicado: (2022)

Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial
por: Wilson, F Perry, et al.
Publicado: (2021)

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation
por: Zhao, Yiqing, et al.
Publicado: (2021)

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids
por: Lam, Carson, et al.
Publicado: (2021)

Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units
por: McCoy, Andrea, et al.
Publicado: (2017)

Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record
por: Jamian, Lia, et al.
Publicado: (2019)

Improving Current Glycated Hemoglobin Prediction in Adults: Use of Machine Learning Algorithms With Electronic Health Records
por: Alhassan, Zakhriya, et al.
Publicado: (2021)

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

Machine Learning Electronic Health Record Identification of Patients with Rheumatoid Arthritis: Algorithm Pipeline Development and Validation Study
por: Maarseveen, Tjardo D, et al.
Publicado: (2020)

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)

Machine Learning Models to Predict Kidney Stone Recurrence Using 24 Hour Urine Testing and Electronic Health Record-Derived Features
por: Doyle, Patrick, et al.
Publicado: (2023)

A Novel Chronic Kidney Disease Phenotyping Algorithm Using Combined Electronic Health Record and Claims Data
por: Mansour, Omar, et al.
Publicado: (2023)

Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial
por: Burdick, Hoyt, et al.
Publicado: (2020)

Machine Learning Algorithms to Predict Breast Cancer Recurrence Using Structured and Unstructured Sources from Electronic Health Records
por: González-Castro, Lorena, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_0rdaflpkuf9f6gtbcfolld0q8v