Staffing & Scheduling

Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review.

INTRODUCTION: Artificial Intelligence (AI) represents the application of computer systems to tasks traditionally performed by humans. The medical imaging profession has experienced a transformative shift through the integration of AI. While there have been several independent primary studies describing various aspects of AI, the current review employs a systematic approach towards describing the p...

A systematic review of generalization research in medical image classification.

Numerous Deep Learning (DL) classification models have been developed for a large spectrum of medical image analysis applications, which promises to reshape various facets of medical practice. Despite early advances in DL model validation and implementation, which encourage healthcare institutions to adopt them, a fundamental questions remain: how can these models effectively handle domain shift? ...

Deciphering the impact of cascade reservoirs on nitrogen transport and nitrate transformation: Insights from multiple isotope analysis and machine learning.

Construction of cascade reservoirs has altered nutrient dynamics and biogeochemical cycles, thereby influencing the composition and productivity of ri...

Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. Th...

Classification of Internal and External Distractions in an Educational VR Environment Using Multimodal Features.

Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR...

Effectiveness of robotic rehabilitation for gait and balance in people with multiple sclerosis: a systematic review.

This review investigated the effectiveness of robotic-assisted gait training (RAGT) in improving gait and balance performance in adults with multiple ...

Learning to match patients to clinical trials using large language models.

OBJECTIVE: This study investigates the use of Large Language Models (LLMs) for matching patients to clinical trials (CTs) within an information retrie...

Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.

Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but addressing heterogeneity in...

Development of a Predictive Hospitalization Model for Skilled Nursing Facility Patients.

OBJECTIVES: Identifying skilled nursing facility (SNF) patients at risk for hospitalization or death is of interest to SNFs, patients, and patients' f...

ReBiA-Robotic Enabled Biological Automation: 3D Epithelial Tissue Production.

The Food and Drug Administration's recent decision to eliminate mandatory animal testing for drug approval marks a significant shift to alternative me...

How can quantum computing be applied in clinical trial design and optimization?

Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success ...

Evaluation of crop water stress index of wheat by using machine learning models.

The Crop Water Stress Index (CWSI), a pivotal indicator derived from canopy temperature, plays a crucial role in irrigation scheduling for water conse...

Real-Time Air-Writing Recognition for Arabic Letters Using Deep Learning.

Learning to write the Arabic alphabet is crucial for Arab children's cognitive development, enhancing their memory and retention skills. However, the ...

Integrating Large Language Model, EEG, and Eye-Tracking for Word-Level Neural State Classification in Reading Comprehension.

With the recent proliferation of large language models (LLMs), such as Generative Pre-trained Transformers (GPT), there has been a significant shift i...

Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network.

The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shi...

Explainability of artificial neural network in predicting career fulfilment among medical doctors in developing nations: Applicability and implications.

BACKGROUND: Career fulfilment among medical doctors is crucial for job satisfaction, retention, and healthcare quality, especially in developing natio...

Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank.

The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Her...

Machine learning-based estimation of evapotranspiration under adaptation conditions: a case study in Heilongjiang Province, China.

The prediction of evapotranspiration (ET0) is crucial for agricultural ecosystems, irrigation management, and environmental climate regulation. Tradit...

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes...

Artificial Intelligence in the Training of Radiology Residents: a Multicenter Randomized Controlled Trial.

The aim of the present study was to compare the effectiveness of AI-assisted training and conventional human training in clinical practice. This was a...