A deep convolutional neural network for the automatic segmentation of glioblastoma brain tumor: Joint spatial pyramid module and attention mechanism network
This study proposes a deep convolutional neural network for the automatic segmentation of
glioblastoma brain tumors, aiming sat replacing the manual segmentation method that is …
glioblastoma brain tumors, aiming sat replacing the manual segmentation method that is …
Prioritising patients for semi‐urgent surgery: A scoping review
EK Coffey, RM Walker, P Nicholson… - Journal of Clinical …, 2024 - Wiley Online Library
Background Semi‐urgent surgery where surgical intervention is required within 48 h of
admission and the patient is medically stable is vulnerable to scheduling delays. Given the …
admission and the patient is medically stable is vulnerable to scheduling delays. Given the …
A data-driven target-oriented robust optimization framework: bridging machine learning and optimization under uncertainty
JL San Juan, C Sy - Journal of Industrial and Production …, 2024 - Taylor & Francis
The target-oriented robust optimization (TORO) approach converts the original objectives to
system targets and instead maximizes an uncertainty budget or robustness index. Machine …
system targets and instead maximizes an uncertainty budget or robustness index. Machine …
Machine Learning to Predict-Then-Optimize Elective Orthopaedic Surgery Scheduling Improves Operating Room Utilization
Objective: To determine the potential for improving elective surgery scheduling for total knee
and hip arthroplasty (TKA and THA, respectively) by utilizing a two-stage approach that …
and hip arthroplasty (TKA and THA, respectively) by utilizing a two-stage approach that …
An Improved Prescriptive Tree-Based Model for Stochastic Parallel Machine Scheduling
Abstract Machine scheduling serves as a vital function for industrial and service operations,
and uncertainties always pose a significant challenge in real-world scheduling practices. In …
and uncertainties always pose a significant challenge in real-world scheduling practices. In …