AIMC Topic: Length of Stay

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Leveraging Hematologic Single-Cell Measurements for Patient Triage and Outcome Prediction.

The journal of applied laboratory medicine
BACKGROUND: The complete blood count (CBC) is widely used across nearly all areas of medicine. While standard CBC markers reflect basic summaries of the blood cells, modern hematology analyzers generate many additional markers from the underlying dat...

The "Outpatient Arthroplasty Risk Assessment" Score for Same Day Outpatient Primary Total Joint Arthroplasty: A Multicenter Study.

The Journal of arthroplasty
BACKGROUND: The Outpatient Arthroplasty Risk Assessment (OARA) Score was developed to risk-stratify patients for safe same-day discharge outpatient total joint arthroplasty (TJA). It has demonstrated predictive ability for length of stay in primary T...

External validation of an AI-based preoperative frailty index using real-world data.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Preoperative frailty assessment is crucial for surgical risk stratification in older adults. Traditional frailty measurements are often too time-consuming and resource-intensive in preoperative settings. This study aimed to externally val...

Development and external validation of a prediction model for prolonged intensive care unit stay in heart failure patients.

European journal of cardiovascular nursing
AIMS: Prolonged intensive care unit (ICU) stays in heart failure patients are associated with poor prognosis and result in high medical expenses. To develop and validate a predictive model for prolonged ICU stays in heart failure patients.

Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction.

The Journal of arthroplasty
BACKGROUND: Revision total knee arthroplasty (rTKA) and revision total hip arthroplasty (rTHA) are among the most resource-intensive orthopaedic procedures. The primary aim of this study was to compare the accuracy of machine learning models between ...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

The Journal of asthma : official journal of the Association for the Care of Asthma
PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged hospitalization in asthma patients.

Predicting Length of Stay in Acute Care Using Day-to-Day Patient Information.

Studies in health technology and informatics
Predicting the Length of Stay (LoS) in healthcare settings is a critical task that supports optimized resource allocation and tailored clinical decision-making. Unlike most studies focused on ICU patients, this work targets acute care settings, addre...

ICU Length of Stay Prediction for Patients with Diabetes Using Machine Learning and Clinical Notes.

Studies in health technology and informatics
Diabetes, a chronic disease, often leads to poor health outcomes and increased healthcare costs, particularly for patients admitted to ICU. Accurate early prediction of ICU length of stay (LOS) is vital for hospital resource management and patient ou...

Validation of the ACS-NSQIP surgical risk calculator for patients with paraoesophageal hernias undergoing robotic repair.

Surgical endoscopy
BACKGROUND: The National Surgical Quality Improvement Program (NSQIP) American College of Surgeons (ACS) risk calculator is a validated method of predicting postoperative complications that was recently updated to a machine-learning structure. The ob...

Understanding deep learning models for Length of Stay prediction on critically ill patients through latent space visualization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Continuous, real-time monitoring of Length of Stay (LoS) for critically ill patients in Intensive Care Units (ICUs) is essential for anticipating patient needs, reduce the risk of adverse events, optimize resource allocation...