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Length of Stay

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Robotic Versus Laparoscopic Approach to Hiatal Hernia Repair: Results After 7 Years of Robotic Experience.

The American surgeon
INTRODUCTION: Robotic hiatal hernia repair offers potential advantages over traditional laparoscopy, most notably enhanced visualization, improved ergonomics, and articulating instruments. The clinical outcomes, however, have not been adequately eval...

Stroke prognostication for discharge planning with machine learning: A derivation study.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Post-stroke discharge planning may be aided by accurate early prognostication. Machine learning may be able to assist with such prognostication. The study's primary aim was to evaluate the performance of machine learning models using admission data t...

Prediction on critically ill patients: The role of "big data".

Journal of critical care
Accurate outcome prediction in Intensive Care Units (ICUs) would allow for better treatment planning, risk adjustment of study populations, and overall improvements in patient care. In the past, prognostic models have focused on mortality using simpl...

Benchmarking machine learning models on multi-centre eICU critical care dataset.

PloS one
Progress of machine learning in critical care has been difficult to track, in part due to absence of public benchmarks. Other fields of research (such as computer vision and natural language processing) have established various competitions and publi...

Perioperative outcomes of robot-assisted vs video-assisted and traditional open thoracic surgery for lung cancer: A systematic review and network meta-analysis.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The superiority of robot-assisted thoracic surgery (RATS) over video-assisted thoracic surgery (VATS) and thoracotomy remains controversial for lung cancer.

Deep Learning for Improved Risk Prediction in Surgical Outcomes.

Scientific reports
The Norwood surgical procedure restores functional systemic circulation in neonatal patients with single ventricle congenital heart defects, but this complex procedure carries a high mortality rate. In this study we address the need to provide an acc...

Using machine learning to predict early readmission following esophagectomy.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: To establish a machine learning (ML)-based prediction model for readmission within 30 days (early readmission or early readmission) of patients based on their profile at index hospitalization for esophagectomy.

Factors and predictors of length of stay in offenders diagnosed with schizophrenia - a machine-learning-based approach.

BMC psychiatry
BACKGROUND: Prolonged forensic psychiatric hospitalizations have raised ethical, economic, and clinical concerns. Due to the confounded nature of factors affecting length of stay of psychiatric offender patients, prior research has called for the app...