Staffing & Scheduling

Stochastic scheduling of autonomous mobile robots at hospitals.

This paper studies the scheduling of autonomous mobile robots (AMRs) at hospitals where the stochastic travel times and service times of AMRs are affected by the surrounding environment. The routes of AMRs are planned to minimize the daily cost of the hospital (including the AMR fixed cost, penalty cost of violating the time window, and transportation cost). To efficiently generate high-quality so...

Disclosing the locale of transmembrane proteins within cellular alcove by machine learning approach: systematic review and meta analysis.

Protein subcellular localization is a promising research question in Proteomics and associated fields, including Biological Sciences, Biomedical Engineering, Computational Biology, Bioinformatics, Proteomics, Artificial Intelligence, and Biophysics. However, computational techniques are preferred to explore this attribute for a massive number of proteins. The byproduct of this conjunction yields d...

Multimodal Data Fusion to Detect Preknowledge Test-Taking Behavior Using Machine Learning.

In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made base...

A GPU-based computational framework that bridges neuron simulation and artificial intelligence.

Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical fr...

Assessment of robotic telesurgery system among surgeons: a single-center study.

The field of robotic-assisted surgery is expanding rapidly; therefore, future robotic surgeons will need to be trained in an organized manner. Here, w...

Machine Learning for the Prediction of Procedural Case Durations Developed Using a Large Multicenter Database: Algorithm Development and Validation Study.

BACKGROUND: Accurate projections of procedural case durations are complex but critical to the planning of perioperative staffing, operating room resou...

Artificial intelligence in cardiac computed tomography.

Artificial Intelligence (AI) is a broad discipline of computer science and engineering. Modern application of AI encompasses intelligent models and al...

Advances in AI-Driven Retention Prediction for Different Chromatographic Techniques: Unraveling the Complexity.

Retention prediction through Artificial intelligence (AI)-based techniques has gained exponential growth due to their abilities to process complex set...

Saline wastewater treatment by bioelectrochemical process (BEC) based on Al-electrocoagulation and halophilic bacteria: optimization using ANN with new approach.

In the present study, a bioelectrochemical reactor (BEC) was utilized to treat two types of real saline produced water (PW). BEC was designed based on...

Surgical scheduling via optimization and machine learning with long-tailed data : Health care management science, in press.

Using data from cardiovascular surgery patients with long and highly variable post-surgical lengths of stay (LOS), we develop a modeling framework to ...

ChatGPT in Head and Neck Oncology-Opportunities and Challenges.

Head and neck oncology represents a complex and challenging field, encompassing the diagnosis, treatment and management of various malignancies affect...

Crash injury severity prediction considering data imbalance: A Wasserstein generative adversarial network with gradient penalty approach.

For each road crash event, it is necessary to predict its injury severity. However, predicting crash injury severity with the imbalanced data frequent...

Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity.

Several studies demonstrate that the structure of the brain increases in hierarchical complexity throughout development. We tested if the structure of...

A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition.

Electromyography (EMG) pattern recognition is an important technology for prosthesis control and human-computer interaction etc. However, the practica...

Robotic Medtronic Hugo™ RAS System Is Now Reality: Introduction to a New Simulation Platform for Training Residents.

The use of robotic surgery (RS) in urology has grown exponentially in the last decade, but RS training has lagged behind. The launch of new robotic pl...

Digital transformation of mental health services.

This paper makes a case for digital mental health and provides insights into how digital technologies can enhance (but not replace) existing mental he...

Incremental learning for an evolving stream of medical ultrasound images via counterfactual thinking.

Despite the fact that traditional deep learning (DL) approaches provide promising accuracy and efficiency in medical ultrasound image analysis, they c...

Machine learning-based radiotherapy time prediction and treatment scheduling management.

PURPOSE: The utility efficiency of medical devices is important, especially for countries such as China, which have a large population and shortage of...

Artificial intelligence directed development of a digital twin to measure soft tissue shift during head and neck surgery.

Digital twins derived from 3D scanning data were developed to measure soft tissue deformation in head and neck surgery by an artificial intelligence a...

Explanations as a New Metric for Feature Selection: A Systematic Approach.

With the extensive use of Machine Learning (ML) in the biomedical field, there was an increasing need for Explainable Artificial Intelligence (XAI) to...