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Length of Stay

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Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).

Critical care medicine
OBJECTIVES: Delirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a to...

Comparison of Perioperative Outcomes for Radical Nephrectomy Based on Surgical Approach for Masses Greater Than 10 cm.

Journal of endourology
Robot-assisted radical nephrectomy (RRN) is increasingly utilized as an alternative to laparoscopic radical nephrectomy (LRN), but there are concerns over costs and objective benefit. In the setting of very large renal masses (>10 cm), comparison be...

[Artificial Intelligence in internal medicine : development of a model predicting length of stay for non-elective admissions].

Revue medicale suisse
Efficient management of hospitalized patients requires carefully planning each stay by taking into account patients' pathologies and hospital constraints. Therefore, the ability to accurately estimate length of stays allows for better interprofession...

The Cost of Robot-assisted Total Hip Arthroplasty: Comparing Safety and Hospital Charges to Conventional Total Hip Arthroplasty.

The Journal of the American Academy of Orthopaedic Surgeons
INTRODUCTION: Utilization of robotic assistance is increasing for total hip arthroplasty (THA). However, few studies have directly examined the efficacy of this technique at reducing complications. This research aims to compare the rates of periopera...

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patien...

Gynecological Surgery and Machine Learning: Complications and Length of Stay Prediction.

Studies in health technology and informatics
In this study we are developing predictive models for a length of stay after a gynecological surgery, complications and the length of the surgery using machine learning methods. The study was performed with the data of patients with the diseases of t...

Predicting 2-Day Mortality of Thrombocytopenic Patients Based on Clinical Laboratory Data Using Machine Learning.

Medical care
BACKGROUND: Clinical laboratories have traditionally used a single critical value for thrombocytopenic events. This system, however, could lead to inaccuracies and inefficiencies, causing alarm fatigue and compromised patient safety.

Drivers of Prolonged Hospitalization Following Spine Surgery: A Game-Theory-Based Approach to Explaining Machine Learning Models.

The Journal of bone and joint surgery. American volume
BACKGROUND: Understanding the interactions between variables that predict prolonged hospital length of stay (LOS) following spine surgery can help uncover drivers of this risk in patients. This study utilized a novel game-theory-based approach to dev...