AIMC Topic: Patient Readmission
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An interpretable machine learning scoring tool for estimating time to recurrence readmissions in stroke patients.
International journal of medical informatics
Nov 16, 2024
BACKGROUND: Stroke recurrence readmission poses an additional burden on both patients and healthcare systems. Risk stratification aims to accurately divide patients into groups to provide targeted interventions at reducing readmission. To accurately ...
Development and validation of a machine learning model to predict the risk of readmission within one year in HFpEF patients: Short title: Prediction of HFpEF readmission.
International journal of medical informatics
Nov 14, 2024
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is associated with elevated rates of readmission and mortality. Accurate prediction of readmission risk is essential for optimizing healthcare resources and enhancing patient outcomes...
Development and Validation of a Predictive Model for Maternal Cardiovascular Morbidity Events in Patients With Hypertensive Disorders of Pregnancy.
Anesthesia and analgesia
Nov 6, 2024
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are a major contributor to maternal morbidity, mortality, and accelerated cardiovascular (CV) disease. Comorbid conditions are likely important predictors of CV risk in pregnant people. Currently,...
Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study.
Journal of clinical anesthesia
Oct 14, 2024
BACKGROUND: Intensive care units (ICUs) harbor the sickest patients with the utmost needs of medical care. Discharge from ICU needs to consider the reason for admission and stability after ICU care. Organ dysfunction or instability after ICU discharg...
Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.
PloS one
Aug 23, 2024
AIM: In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause somatic hospital admissions and readmissions in adults.
Utility of Machine Learning, Natural Language Processing, and Artificial Intelligence in Predicting Hospital Readmissions After Orthopaedic Surgery: A Systematic Review and Meta-Analysis.
JBJS reviews
Aug 22, 2024
BACKGROUND: Numerous applications and strategies have been utilized to help assess the trends and patterns of readmissions after orthopaedic surgery in an attempt to extrapolate possible risk factors and causative agents. The aim of this work is to s...
Prediction of 90 day readmission in heart failure with preserved ejection fraction by interpretable machine learning.
ESC heart failure
Aug 21, 2024
AIMS: Certain critical risk factors of heart failure with preserved ejection fraction (HFpEF) patients were significantly different from those of heart failure with reduced ejection fraction (HFrEF) patients, resulting in the limitations of existing ...
Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.
American heart journal
Jul 31, 2024
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...
SHAP based predictive modeling for 1 year all-cause readmission risk in elderly heart failure patients: feature selection and model interpretation.
Scientific reports
Jul 31, 2024
Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission ris...
Machine learning analysis of lab tests to predict bariatric readmissions.
Scientific reports
Jul 22, 2024
The purpose of this study was to develop a machine learning model for predicting 30-day readmission after bariatric surgery based on laboratory tests. Data were collected from patients who underwent bariatric surgery between 2018 and 2023. Laboratory...
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