AIMC Topic: Length of Stay
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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
Jun 12, 2021
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
May 27, 2021
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
Mar 1, 2021
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
Jan 6, 2021
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...
ROBOTIC LIVER RESECTION. REPORT OF THE FIRST 50 CASES.
Arquivos de gastroenterologia
Jan 1, 2021
BACKGROUND: Robotic surgery has gained growing acceptance in recent years, expanding to liver resection.
Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach.
Respiratory care
Sep 1, 2020
BACKGROUND: Bedside monitors in the ICU routinely measure and collect patients' physiologic data in real time to continuously assess the health status of patients who are critically ill. With the advent of increased computational power and the abilit...
Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Predicting Cardiovascular Length of stay based hospitalization at the time of patients' admitting to the coronary care unit (CCU) or (cardiac intensive care units CICU) is deemed as a challenging task to hospital management systems globally. Recently...
Dr. Agent: Clinical predictive model via mimicked second opinions.
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2020
OBJECTIVE: Prediction of disease phenotypes and their outcomes is a difficult task. In practice, patients routinely seek second opinions from multiple clinical experts for complex disease diagnosis. Our objective is to mimic such a practice of seekin...
A Novel Machine Learning Model Developed to Assist in Patient Selection for Outpatient Total Shoulder Arthroplasty.
The Journal of the American Academy of Orthopaedic Surgeons
Jul 1, 2020
INTRODUCTION: Patient selection for outpatient total shoulder arthroplasty (TSA) is important to optimizing patient outcomes. This study aims to develop a machine learning tool that may aid in patient selection for outpatient total should arthroplast...
The Impact of Robotics in Learning Roux-en-Y Gastric Bypass: a Retrospective Analysis of 214 Laparoscopic and Robotic Procedures : Robotic Vs. Laparoscopic RYGB.
Obesity surgery
Jun 1, 2020
BACKGROUND: Proximal Roux-en-Y gastric bypass is commonly used to manage obesity, performed using laparoscopic or robot-assisted minimally invasive surgery. As the prevalence of robotic bariatric surgery increases, further data is required to justify...
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