AIMC Topic: Operating Rooms

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Measuring provider-level differences in perioperative workflow using computer vision-based artificial intelligence.

BMJ health & care informatics
OBJECTIVES: To evaluate provider-level variability across the full perioperative workflow using a computer vision-based artificial intelligence (AI) system that automatically detects and timestamps operating room events.

Fast operating room scattered radiation calculation in x-ray guided interventions by using deep learning.

Journal of radiological protection : official journal of the Society for Radiological Protection
Protecting medical personnel from the harmful effects of scattered ionising radiation during x-ray-guided procedures is a critical concern. Due to the complex and invisible nature of x-rays, monitoring radiation exposure has been challenging. Existin...

Harnessing operating room signals to estimate mean arterial pressure with AnesthNet.

Scientific reports
Monitoring mean arterial pressure (MAP) is essential for ensuring safe general anesthesia. Current practices rely either on non-invasive cuff measurements, which suffer from poor temporal resolution, or invasive arterial lines, which provide excellen...

Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study.

JMIR medical informatics
BACKGROUND: Total knee and hip arthroplasty (TKA and THA) are among the most performed elective procedures. Rising demand and the resource-intensive nature of these procedures have contributed to longer wait times despite significant health care inve...

The AI-enhanced surgeon - integrating black-box artificial intelligence in the operating room.

International journal of surgery (London, England)
New artificial intelligence (AI)/machine learning (ML) technology offers great potential to assist surgeons with real-time intra-operative decision-making. While, AI/ML-driven analysis tools for surgeons currently focus primarily on technical assista...

Innovative Technologies for Smarter and Efficient Operating Room Scheduling.

Journal of medical systems
An optimized scheduling system for surgical procedures is considered fundamental for maximizing hospital resource utilization and improving patient outcomes. The integration of Artificial Intelligence (AI) tools and New Technologies is paramount in t...

Predicting Robotic Hysterectomy Incision Time: Optimizing Surgical Scheduling with Machine Learning.

JSLS : Journal of the Society of Laparoendoscopic Surgeons
BACKGROUND AND OBJECTIVES: Operating rooms (ORs) are critical for hospital revenue and cost management, with utilization efficiency directly affecting financial outcomes. Traditional surgical scheduling often results in suboptimal OR use. We aim to b...

Development of Predictive Model of Surgical Case Durations Using Machine Learning Approach.

Journal of medical systems
Optimizing operating room (OR) utilization is critical for enhancing hospital management and operational efficiency. Accurate surgical case duration predictions are essential for achieving this optimization. Our study aimed to refine the accuracy of ...

Development and validation of an artificial intelligence system for surgical case length prediction.

Surgery
BACKGROUND: Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for ...

Towards multimodal graph neural networks for surgical instrument anticipation.

International journal of computer assisted radiology and surgery
PURPOSE: Decision support systems and context-aware assistance in the operating room have emerged as the key clinical applications supporting surgeons in their daily work and are generally based on single modalities. The model- and knowledge-based in...