Predicting Procedure Duration to Improve Scheduling of Elective Surgery

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Pacific Rim International Conference on Artificial Intelligence

• Publication date

  2014-12-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1007/978-3-319-13560-1_86
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Adaptive Regression Splines toolbox for Matlab/Octave

  2015cited by this paper
• Value of a Scheduled Duration Quantified in Terms of Equivalent Numbers of Historical Cases

  2013cited by this paper
• Using Mathematical Competencies to Predict Item Difficulty in PISA: A MEG Study

  2013cited by this paper
• Prediction of Surgery Times and Scheduling of Operation Theaters in Optholmology Department

  2012cited by this paper
• Integrating Data Mining and Optimization Techniques on Surgery Scheduling

  2012cited by this paper
• Improving Prediction of Surgery Duration using Operational and Temporal Factors

  2012cited by this paper
• Operating room planning and scheduling: A literature review

  2010cited by this paper
• Predicting the Unpredictable: A New Prediction Model for Operating Room Times Using Individual Characteristics and the Surgeon's Estimate

  2010cited by this paper
• A method for spatial prediction of daily soil water status for precise irrigation scheduling

  2009cited by this paper
• Research Corner: Regression Analysis for Prediction: Understanding the Process

  2009cited by this paper
• Modeling and prediction of surgical procedure times

  2009cited by this paper
• Predicting surgical case durations using ill-conditioned CPT code matrix

  2009cited by this paper
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition

  2009cited by this paper
• Using KDD process to forecast a duration of surgery

  2008cited by this paper
• Systematic Review of General Thoracic Surgery Articles to Identify Predictors of Operating Room Case Durations

  2008cited by this paper
• Estimating the duration of common elective operations: implications for operating list management

  2006cited by this paper
• Cancellation of operations on the day of intended surgery at a major Australian referral hospital

  2005cited by this paper
• Bayesian Prediction Bounds and Comparisons of Operating Room Times Even for Procedures with Few or No Historic Data

  2005cited by this paper
• Random Forests

  2001cited by this paper
• Modeling the Uncertainty of Surgical Procedure Times: Comparison of Log-normal and Normal Models

  2000cited by this paper
• Relying solely on historical surgical times to estimate accurately future surgical times is unlikely to reduce the average length of time cases finish late.

  1999cited by this paper
• Statistical Modeling to Predict Elective Surgery Time: Comparison with a Computer Scheduling System and Surgeon-provided Estimates

  1996cited by this paper
• Where Are the Costs in Perioperative Care?: Analysis of Hospital Costs and Charges for Inpatient Surgical Care

  1995cited by this paper
• Support-Vector Networks

  1995cited by this paper
• Nonexercise regression models to estimate peak oxygen consumption.

  1995cited by this paper
• Multivariate adaptive regression splines

  1990cited by this paper
• A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

  1987cited by this paper
• Learning internal representations by error propagation

  1986cited by this paper

• Prediction of remaining surgery duration based on machine learning methods and laparoscopic annotation data

  2025cites this paper
• A Hybrid Machine Learning Model for Predicting Surgical Procedure Duration: Integrating Random Forest and K-Means Clustering

  2025cites this paper
• Multimodal Feature Analysis for Surgery Duration Predication

  2024cites this paper
• Machine Learning to Predict Surgery Duration: Towards Implementing AI and Digital Twin for Effective Scheduling

  2024cites this paper
• Improving preoperative prediction of surgery duration

  2023influential citation
• Technological Trend Analysis for Surgical Operation Duration Estimation

  2023cites this paper
• Leveraging large, real-world data through machine-learning to increase efficiency in robotic-assisted total knee arthroplasty

  2023cites this paper
• Estimation of Surgery Durations Using Machine Learning Methods-A Cross-Country Multi-Site Collaborative Study

  2022cites this paper
• Daily surgery caseload prediction: towards improving operating theatre efficiency

  2022cites this paper
• Quantile regression forests for individualized surgery scheduling

  2022cites this paper
• Application of Machine Learning Methods on Patient Reported Outcome Measurements for Predicting Outcomes: A Literature Review

  2021cites this paper
• Key Experimental Factors of Machine Learning-Based Identification of Surgery Cancellations

  2021cites this paper
• Bayesian hierarchical modeling of operating room times for surgeries with few or no historic data

  2021cites this paper
• An evaluation of a simple model for predicting surgery duration using a set of surgical procedure parameters

  2021cites this paper
• Predictive Analytics on Scheduled Surgery Cases in Forecasting the Operating Theatre Utilisation

  2021cites this paper
• Operating Room Scheduling by Considering Surgical Inventory, Post Anesthesia Beds, and Emergency Surgeries to Improve Efficiency During the COVID-19 Outbreak with Machine Learning

  2021cites this paper
• Comparison of Jackknife and Hybrid-Boost Model Averaging to Predict Surgery Durations: A Case Study

  2020cites this paper
• Predicting Crime Scene Location Details for First Responders

  2020cites this paper
• An Evaluation of the Hybrid Model for Predicting Surgery Duration

  2020cites this paper
• Exemplars of Artificial Intelligence and Machine Learning in Healthcare

  2020cites this paper
• Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning

  2019cites this paper
• Acute postoperative pain management at a tertiary hospital in Addis Ababa, Ethiopia: A prospective crosssectional study

  2019cites this paper
• Application of Operational Research Techniques in Operating Room Scheduling Problems: Literature Overview

  2018cites this paper
• Integrated Machine Learning and Optimization Frameworks with Applications in Operations Management

  2018cites this paper
• Predicting the duration of surgeries to Improve Process Efficiency in Hospitals

  2017cites this paper
• Intelligent Scheduling for Hospital Operating Rooms

  2016cites this paper