Cargando…

Predictive modeling in urgent care: a comparative study of machine learning approaches

OBJECTIVE: The growing availability of rich clinical data such as patients’ electronic health records provide great opportunities to address a broad range of real-world questions in medicine. At the same time, artificial intelligence and machine learning (ML)-based approaches have shown great premis...

Descripción completa

Detalles Bibliográficos
Autores principales:	Tang, Fengyi, Xiao, Cao, Wang, Fei, Zhou, Jiayu
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2018
Materias:	Research and Applications
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6951928/ https://www.ncbi.nlm.nih.gov/pubmed/31984321 http://dx.doi.org/10.1093/jamiaopen/ooy011

Ejemplares similares

TB-ML—a framework for comparing machine learning approaches to predict drug resistance of Mycobacterium tuberculosis
por: Libiseller-Egger, Julian, et al.
Publicado: (2023)

An approach to predicting patient experience through machine learning and social network analysis
por: Bari, Vitej, et al.
Publicado: (2020)

Comparison and interpretability of machine learning models to predict severity of chest injury
por: Kulshrestha, Sujay, et al.
Publicado: (2021)

Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results
por: Zikmund-Fisher, Brian J, et al.
Publicado: (2017)

Development of a novel machine learning model to predict presence of nonalcoholic steatohepatitis
por: Docherty, Matt, et al.
Publicado: (2021)

GNL-Scorer: a generalized model for predicting CRISPR on-target activity by machine learning and featurization
por: Wang, Jun, et al.
Publicado: (2020)

Implementation approaches and barriers for rule-based and machine learning-based sepsis risk prediction tools: a qualitative study
por: Joshi, Mugdha, et al.
Publicado: (2022)

Developing machine learning models to personalize care levels among emergency room patients for hospital admission
por: Nguyen, Minh, et al.
Publicado: (2021)

Evaluation of a machine learning approach utilizing wearable data for prediction of SARS-CoV-2 infection in healthcare workers
por: Hirten, Robert P, et al.
Publicado: (2022)

POOL server: machine learning application for functional site prediction in proteins
por: Somarowthu, Srinivas, et al.
Publicado: (2012)

Trends in anesthesiology research: a machine learning approach to theme discovery and summarization
por: Rusanov, Alexander, et al.
Publicado: (2018)

Species complex delimitations in the genus Hedychium: A machine learning approach for cluster discovery
por: Saryan, Preeti, et al.
Publicado: (2020)

Scalable machine learning-assisted model exploration and inference using Sciope
por: Singh, Prashant, et al.
Publicado: (2020)

Aliro: an automated machine learning tool leveraging large language models
por: Choi, Hyunjun, et al.
Publicado: (2023)

Predicting 72-hour and 9-day return to the emergency department using machine learning
por: Hong, Woo Suk, et al.
Publicado: (2019)

Machine Learning Approach Effectively Predicts Binding Between SARS-CoV-2 Spike and ACE2 Across Mammalian Species — Worldwide, 2021
por: Ma, Yue, et al.
Publicado: (2021)

HPiP: an R/Bioconductor package for predicting host–pathogen protein–protein interactions from protein sequences using ensemble machine learning approach
por: Rahmatbakhsh, Matineh, et al.
Publicado: (2022)

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study
por: Roimi, Michael, et al.
Publicado: (2021)

Piloting a model-to-data approach to enable predictive analytics in health care through patient mortality prediction
por: Bergquist, Timothy, et al.
Publicado: (2020)

Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods
por: Song, Wenyu, et al.
Publicado: (2022)

A machine learning approach to determine resilience utilizing wearable device data: analysis of an observational cohort
por: Hirten, Robert P, et al.
Publicado: (2023)

Natural language processing and machine learning of electronic health records for prediction of first-time suicide attempts
por: Tsui, Fuchiang R, et al.
Publicado: (2021)

ODNA: identification of organellar DNA by machine learning
por: Martin, Roman, et al.
Publicado: (2023)

Comparative Analysis of COVID-19 X-ray Images Classification Using Convolutional Neural Network, Transfer Learning, and Machine Learning Classifiers Using Deep Features
por: Rekha Rajagopal
Publicado: (2021)

Bias or biology? Importance of model interpretation in machine learning studies from electronic health records
por: Momenzadeh, Amanda, et al.
Publicado: (2022)

DeepPurpose: a deep learning library for drug–target interaction prediction
por: Huang, Kexin, et al.
Publicado: (2020)

Machine learning for initial insulin estimation in hospitalized patients
por: Nguyen, Minh, et al.
Publicado: (2021)

Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults
por: Chun, Matthew, et al.
Publicado: (2021)

New onset delirium prediction using machine learning and long short-term memory (LSTM) in electronic health record
por: Liu, Siru, et al.
Publicado: (2022)

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record
por: Corbin, Conor K, et al.
Publicado: (2023)

Application of machine learning methods in clinical trials for precision medicine
por: Wang, Yizhuo, et al.
Publicado: (2022)

mOWL: Python library for machine learning with biomedical ontologies
por: Zhapa-Camacho, Fernando, et al.
Publicado: (2022)

Genome mining for anti-CRISPR operons using machine learning
por: Yang, Bowen, et al.
Publicado: (2023)

Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts
por: Baron, Jason M, et al.
Publicado: (2021)

From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2
por: Weaver, William N., et al.
Publicado: (2023)

ClinicNet: machine learning for personalized clinical order set recommendations
por: Wang, Jonathan X, et al.
Publicado: (2020)

Machine learning for early detection of sepsis: an internal and temporal validation study
por: Bedoya, Armando D, et al.
Publicado: (2020)

Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia
por: Coombes, Caitlin E, et al.
Publicado: (2020)

mlr3proba: an R package for machine learning in survival analysis
por: Sonabend, Raphael, et al.
Publicado: (2021)

Machine learning identifies girls with central precocious puberty based on multisource data
por: Pan, Liyan, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_755fv73i3rld1fs4t7tfnv4373