Staffing & Scheduling

Prospects of cold plasma in enhancing food phenolics: analyzing nutritional potential and process optimization through RSM and AI techniques.

Consumption of plant-based food is steadily increasing and follows an augmented trend owing to their...

Characterizing the microbiome recruited by the endangered plant in phosphorus-deficient acidic soil.

Phosphorus (P)-deficient soils serve as crucial habitats for endangered plant species. Microbiomes p...

Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial.

BACKGROUND: With increasing adoption of remote clinical trials in digital mental health, identifying...

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

Optimizing operating room (OR) utilization is critical for enhancing hospital management and operati...

Illustration image style transfer method design based on improved cyclic consistent adversarial network.

To improve the expressiveness and realism of illustration images, the experiment innovatively combin...

The integration and innovative practice of intelligent AI and local opera in college teaching.

This paper explores the impacts of integrating AI into the teaching of Chinese Opera using a mixed-m...

In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability.

Deep learning (DL)-based Human Activity Recognition (HAR) using wearable inertial measurement unit (...

AI Interventions to Alleviate Healthcare Shortages and Enhance Work Conditions in Critical Care: Qualitative Analysis.

BACKGROUND: The escalating global scarcity of skilled health care professionals is a critical concer...

Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect.

Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean h...

Artificial Intelligence-Driven Translation Tools in Intensive Care Units for Enhancing Communication and Research.

UNLABELLED: There is a need to improve communication for patients and relatives who belong to cultur...

Improving 3D deep learning segmentation with biophysically motivated cell synthesis.

Biomedical research increasingly relies on three-dimensional (3D) cell culture models and artificial...

Leveraging Large Language Models to Enhance Dermatology Clinical Trial Patient Recruitment and Retention.

The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models.

Complex deep learning models trained on very large datasets have become key enabling tools for curre...

A comprehensive retrospect on the current perspectives and future prospects of pneumoconiosis.

Pneumoconiosis is a widespread occupational pulmonary disease caused by inhalation and retention of ...

G-SET-DCL: a guided sequential episodic training with dual contrastive learning approach for colon segmentation.

PURPOSE: This article introduces a novel deep learning approach to substantially improve the accurac...

A Symbolic AI Approach to Medical Training.

In traditional medical education, learners are mostly trained to diagnose and treat patients through...

ImpACT Project: Improving Access to Clinical Trials in Victoria, an Artificial Intelligence-Based Approach.

PURPOSE: Enhancing the speed and efficiency of clinical trial recruitment is a key objective across ...

Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches.

Deep learning-based medical image analysis has shown strong potential in disease categorization, seg...

Revolutionizing surgery: AI and robotics for precision, risk reduction, and innovation.

Artificial intelligence and robotics are revolutionizing surgical practices by enhancing precision, ...

Avoiding catastrophic overfitting in fast adversarial training with adaptive similarity step size.

Adversarial training has become a primary method for enhancing the robustness of deep learning model...

Open-source Large Language Models can Generate Labels from Radiology Reports for Training Convolutional Neural Networks.

RATIONALE AND OBJECTIVES: Training Convolutional Neural Networks (CNN) requires large datasets with ...