[HTML][HTML] Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models
Abstract Background and Objectives We sought to summarize the study design, modelling
strategies, and performance measures reported in studies on clinical prediction models …
strategies, and performance measures reported in studies on clinical prediction models …
Use of electronic medical records in development and validation of risk prediction models of hospital readmission: systematic review
Objective To provide focused evaluation of predictive modeling of electronic medical record
(EMR) data to predict 30 day hospital readmission. Design Systematic review. Data source …
(EMR) data to predict 30 day hospital readmission. Design Systematic review. Data source …
Application of machine learning in predicting hospital readmissions: a sco** review of the literature
Background Advances in machine learning (ML) provide great opportunities in the
prediction of hospital readmission. This review synthesizes the literature on ML methods and …
prediction of hospital readmission. This review synthesizes the literature on ML methods and …
Data mining and machine learning techniques applied to public health problems: A bibliometric analysis from 2009 to 2018
The objective of this paper is to present a bibliometric analysis of the applications of Data
Mining (DM) and Machine Learning (ML) techniques in the context of public health from …
Mining (DM) and Machine Learning (ML) techniques in the context of public health from …
A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models
Objective Health care providers increasingly rely upon predictive algorithms when making
important treatment decisions, however, evidence indicates that these tools can lead to …
important treatment decisions, however, evidence indicates that these tools can lead to …
Joint imbalanced classification and feature selection for hospital readmissions
Hospital readmission is one of the most important service quality measures. Recently,
numerous risk assessment models have been proposed to address the hospital readmission …
numerous risk assessment models have been proposed to address the hospital readmission …
An explanatory machine learning framework for studying pandemics: The case of COVID-19 emergency department readmissions
One of the major challenges that confront medical experts during a pandemic is the time
required to identify and validate the risk factors of the novel disease and to develop an …
required to identify and validate the risk factors of the novel disease and to develop an …
Clinical implementation of predictive models embedded within electronic health record systems: a systematic review
Predictive analytics using electronic health record (EHR) data have rapidly advanced over
the last decade. While model performance metrics have improved considerably, best …
the last decade. While model performance metrics have improved considerably, best …
Implementation of artificial intelligence-based clinical decision support to reduce hospital readmissions at a regional hospital
S Romero-Brufau, KD Wyatt, P Boyum… - Applied clinical …, 2020 - thieme-connect.com
Background Hospital readmissions are a key quality metric, which has been tied to
reimbursement. One strategy to reduce readmissions is to direct resources to patients at the …
reimbursement. One strategy to reduce readmissions is to direct resources to patients at the …
Epidemiological determinants of patient non-conveyance to the hospital in an emergency medical service environment
Background: The increasing prevalence of comorbidities worldwide has spurred the need
for time-effective pre-hospital emergency medical services (EMS). Some pre-hospital …
for time-effective pre-hospital emergency medical services (EMS). Some pre-hospital …