Predictive models for hospital readmission risk: A systematic review of methods
Objectives Hospital readmission risk prediction facilitates the identification of patients
potentially at high risk so that resources can be used more efficiently in terms of cost-benefit …
potentially at high risk so that resources can be used more efficiently in terms of cost-benefit …
Machine learning methods for hospital readmission prediction: systematic analysis of literature
T Chen, S Madanian, D Airehrour… - Journal of Reliable …, 2022 - Springer
Hospital readmission is one of the challenges that force an extra pressure and financial
burden on healthcare and causes a significant waste of medical resources. However, some …
burden on healthcare and causes a significant waste of medical resources. However, some …
Landslide susceptibility map**: application of novel hybridization of rotation forests (RF) and Java decision trees (J48)
LJ Liang, H Cui, A Arabameri, A Arora… - Soft Computing, 2023 - Springer
In this study, we presented a novel hybrid artificial intelligence method for landslide
susceptibility map** (LSM) in the Kalaleh Watershed, Golestan Province, Iran. This …
susceptibility map** (LSM) in the Kalaleh Watershed, Golestan Province, Iran. This …
Machine learning readmission risk modeling: a pediatric case study
Background. Hospital readmission prediction in pediatric hospitals has received little
attention. Studies have focused on the readmission frequency analysis stratified by disease …
attention. Studies have focused on the readmission frequency analysis stratified by disease …
Balanced training of a hybrid ensemble method for imbalanced datasets: a case of emergency department readmission prediction
Dealing with imbalanced datasets is a recurrent issue in health-care data processing. Most
literature deals with small academic datasets, so that results often do not extrapolate to the …
literature deals with small academic datasets, so that results often do not extrapolate to the …
Active learning for road lane landmark inventory with V-ELM in highly uncontrolled image capture conditions
Road landmark inventory is becoming an important data product for the maintenance of
transport infrastructures. Several commercial sensors are available which include …
transport infrastructures. Several commercial sensors are available which include …
Risk factors for prediction of delirium at hospital admittance
Aging population in many developed countries, moves the issue of healthy aging at the
forefront of the political, scientific and technological concerns. Delirium is a multifactorial …
forefront of the political, scientific and technological concerns. Delirium is a multifactorial …
Neural and statistical predictors for time to readmission in emergency departments: a case study
The prediction of readmissions in the healthcare system, ie patients that are discharged and
come back in a short interval of time, has taken great importance as readmissions have …
come back in a short interval of time, has taken great importance as readmissions have …
Modelling hospital readmissions under frailty conditions for healthy aging
M Grana, JM Lopez‐Guede, J Irazusta… - Expert …, 2020 - Wiley Online Library
In the current context of an aging population in many developed countries, the issue of
healthy aging is at the forefront of the political, scientific, and technological concerns. The …
healthy aging is at the forefront of the political, scientific, and technological concerns. The …
Risk Factors and Survival After Premature Hospital Readmission in Frail Subjects with Delirium
G Cano-Escalera, M Grana, A Besga - International Conference on Hybrid …, 2023 - Springer
In this study we assess the mortality risk after 6 months, 1 year, and 2 years of follow-up in a
sample of frail patients diagnosed with delirium who had been readmitted to hospital before …
sample of frail patients diagnosed with delirium who had been readmitted to hospital before …