AIMC Topic: Patient Readmission

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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...
Retrospective Studies Intensive Care Units Female Aged Humans Machine Learning Patient Discharge Critical Care Patient Readmission Austria Adult Male Middle Aged Cohort Studies
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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.
Patient Readmission Hospitalization Humans Adult Machine Learning ROC Curve Algorithms Natural Language Processing
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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...
Artificial Intelligence Machine Learning Natural Language Processing Patient Readmission Humans Orthopedic Procedures
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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 ...
Aged Patient Readmission Male Stroke Volume Prognosis Middle Aged Retrospective Studies Risk Assessment Female Time Factors Risk Factors Follow-Up Studies Humans Heart Failure Machine Learning
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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...
Humans Middle Aged Machine Learning Risk Assessment Hospitalization Retrospective Studies Acute Disease Ontario Aged Female Heart Failure Models, Statistical Patient Readmission Aged, 80 and over Male
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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...
Risk Factors Aged Aged, 80 and over Male Risk Assessment ROC Curve Heart Failure Patient Readmission Humans Machine Learning Retrospective Studies Female
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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...
Support Vector Machine Bariatric Surgery Patient Readmission Adult Humans Male Machine Learning Middle Aged Female ROC Curve
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Deep learning for predicting rehospitalization in acute heart failure: Model foundation and external validation.

ESC heart failure Jul 9, 2024
AIMS: Assessing the risk for HF rehospitalization is important for managing and treating patients with HF. To address this need, various risk prediction models have been developed. However, none of them used deep learning methods with real-world data...
Heart Failure Patient Readmission Risk Assessment Deep Learning Follow-Up Studies Acute Disease Aged Male Middle Aged Humans Prognosis Retrospective Studies Female Risk Factors
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Established machine learning models to predict readmission for elderly patients with ischemic heart disease.

Kardiologia polska Jul 8, 2024
BACKGROUND: The contribution of clinical features associated with 30-day or 1-year readmission in elderly patients with ischemic heart disease (IHD) and whether these features can be used to predict the readmission risk of patients has not been studi...
Male Humans Patient Readmission Machine Learning Prognosis Myocardial Ischemia Female Aged Aged, 80 and over
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Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.

Diseases of the colon and rectum Jul 3, 2024
BACKGROUND: Early predictors of postoperative complications can risk-stratify patients undergoing colorectal cancer surgery. However, conventional regression models have limited power to identify complex nonlinear relationships among a large set of v...
Risk Assessment Postoperative Complications ROC Curve Logistic Models Colorectal Neoplasms Male Middle Aged Elective Surgical Procedures Patient Readmission Anastomotic Leak Humans Neural Networks, Computer Retrospective Studies Female Aged
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