Staffing & Scheduling

Stochastic scheduling of autonomous mobile robots at hospitals.

This paper studies the scheduling of autonomous mobile robots (AMRs) at hospitals where the stochast...

ChatGPT's performance in dentistry and allergyimmunology assessments: a comparative study.

Large language models (LLMs) such as ChatGPT have potential applications in healthcare, including de...

Conserve the open media ecosystem! Legal and ethical considerations when using online repositories for AI training in ecological research.

Ecological researchers who train Artificial Intelligence models using digital media have to be cogni...

Deep Learning Application to Detect Glaucoma with a Mixed Training Approach: Public Database and Expert-Labeled Glaucoma Population.

INTRODUCTION: Artificial intelligence has real potential for early identification of ocular diseases...

Evaluation of Proclarix in the diagnostic work-up of prostate cancer.

OBJECTIVES: The use of multiparametric magnetic resonance imaging (mpMRI) has been widely adopted in...

Robotic Lung Transplantation: A Paradigm Shift in Surgical Strategy.

Approaches and Limitations of Machine Learning for Synthetic Ultrasound Generation: A Scoping Review.

This scoping review examines the emerging field of synthetic ultrasound generation using machine lea...

A self-training algorithm based on the two-stage data editing method with mass-based dissimilarity.

A self-training algorithm is a classical semi-supervised learning algorithm that uses a small number...

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 field...

Artificial intelligence in small molecule drug discovery from 2018 to 2023: Does it really work?

Utilizing artificial intelligence (AI) in drug design represents an advanced approach for identifyin...

Design and Validation of a Soft Robotic Simulator for Transseptal Puncture Training.

OBJECTIVE: Transseptal puncture (TP) is the technique used to access the left atrium of the heart fr...

Machine learning (ML) techniques to predict breast cancer in imbalanced datasets: a systematic review.

Knowledge discovery in databases (KDD) is crucial in analyzing data to extract valuable insights. In...

A novel Data and Model Centric artificial intelligence based approach in developing high-performance Named Entity Recognition for Bengali Language.

Named Entity Recognition (NER) plays a significant role in enhancing the performance of all types of...

Self-supervised depth super-resolution with contrastive multiview pre-training.

Many low-level vision tasks, including guided depth super-resolution (GDSR), struggle with the issue...

Specialist hybrid models with asymmetric training for malaria prevalence prediction.

Malaria is a common and serious disease that primarily affects developing countries and its spread i...

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

In various fields, including college admission, medical board certifications, and military recruitme...

Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification.

Spiking neural networks (SNNs), as the third generation of neural networks, are based on biological ...

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

Biophysically detailed multi-compartment models are powerful tools to explore computational principl...

An Overview of Robotic Colorectal Surgery Adoption and Training in Brazil.

Robotic surgical systems have rapidly become integrated into colorectal surgery practice in recent ...

Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.

Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and e...

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 ...