AIMC Topic: Length of Stay
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Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.
BMC musculoskeletal disorders
May 21, 2024
BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperatively anticipate adverse postoperative outcomes given the procedure's expanding use. Our study aims to ...
Machine learning prediction of hospitalization costs for coronary artery bypass grafting operations.
Surgery
May 16, 2024
BACKGROUND: With the steady rise in health care expenditures, the examination of factors that may influence the costs of care has garnered much attention. Although machine learning models have previously been applied in health economics, their applic...
Utilizing a comprehensive machine learning approach to identify patients at high risk for extended length of stay following spinal deformity surgery in pediatric patients with early onset scoliosis.
Spine deformity
May 3, 2024
PURPOSE: Early onset scoliosis (EOS) patient diversity makes outcome prediction challenging. Machine learning offers an innovative approach to analyze patient data and predict results, including LOS in pediatric spinal deformity surgery.
Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP.
The Laryngoscope
Apr 23, 2024
OBJECTIVE: Accurate prediction of hospital length of stay (LOS) following surgical management of oral cavity cancer (OCC) may be associated with improved patient counseling, hospital resource utilization and cost. The objective of this study was to c...
Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database.
Medical & biological engineering & computing
Apr 1, 2024
Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. Although predictive machine learning (ML) models show promise for risk stratification in specific po...
Predicting 30-day unplanned hospital readmission after revision total knee arthroplasty: machine learning model analysis of a national patient cohort.
Medical & biological engineering & computing
Mar 7, 2024
Revision total knee arthroplasty (TKA) is associated with a higher risk of readmission than primary TKA. Identifying individual patients predisposed to readmission can facilitate proactive optimization and increase care efficiency. This study develop...
Efficacy of the Addition of Robot-assisted Radical Cystectomy with Extracorporeal Urinary Diversion after an Enhanced Recovery Protocol.
Urology journal
Feb 28, 2024
PURPOSE: It is unclear if robotic radical cystectomy with extracorporeal urinary diversion (eRARC) provides additional benefit when performed along with enhanced recovery after surgery (ERAS). We assessed the additional efficacy of eRARC in terms of ...
Upper gastrointestinal haemorrhage patients' survival: A causal inference and prediction study.
European journal of clinical investigation
Feb 20, 2024
BACKGROUND: Upper gastrointestinal (GI) bleeding is a common medical emergency. This study aimed to develop models to predict critically ill patients with upper GI bleeding in-hospital and 30-day survival, identify the correlation factor and infer th...
Results of robotic liver surgery in association with IWATE criteria - the first 100 cases.
Langenbeck's archives of surgery
Feb 2, 2024
BACKGROUND: Aim of the current study was to present the results of the implementation phase of a robotic liver surgery program and to assess the validity of the IWATE difficulty score in predicting difficulty and postoperative complications in roboti...
Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study.
Frontiers in public health
Jan 5, 2024
OBJECTIVE: The study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources.
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