Staffing & Scheduling

Research on deep learning architecture optimization method for intelligent scheduling of structural space.

Deep neural networks have demonstrated impressive performance across various fields such as computer vision, natural language processing, and autonomous systems. However, their static architectural configurations often result in computational inefficiencies and lack of flexibility, which limit their applicability in intelligent scheduling tasks involving complex structural spaces. To address these...

Approaches in analyzing predictors of trial failure: a scoping review and meta-epidemiological study.

BACKGROUND: Although there are numerous studies exploring predictors of clinical trial failure, no comprehensive review of their methodological specificities and findings exists. We performed a scoping review with the aim of exploring the methodological approaches and findings of studies analysing predictors of clinical trial failure. METHODS: The Ovid Medline and Embase databases were systematica...

A multi-agent reinforcement learning scheduling algorithm integrating state graph and task graph structural modeling for ride-sharing dispatching.

Artificial Intelligence-Assisted Clinical Decision Model for Managing Retained Second Deciduous Molars With No Permanent Successors.

INTRODUCTION: The aim of this study was to develop and apply an artificial intelligence (AI) algorithm to aid the clinical decision-making process for...

AminoacidDB: a liquid chromatography-tandem mass spectrometry-based toolkit for the untargeted analysis of non-protein amino acids.

Non-protein amino acids (npAAs) are produced by microbes, plants and humans, with previous estimates suggesting that there are ≈1000 of such metabolit...

Integrating random forest-based regression kriging for analyzing spatial variability of rainfall in arid and semi-arid regions.

Understanding the spatial variability of precipitation is essential for water resource management and climate adaptation, especially in arid and semi-...

Applications, attitudes and ethical considerations of Generative Artificial Intelligence (Gen AI) in nursing education: a scoping review.

BACKGROUND: Generative Artificial Intelligence (Gen AI) is a type of artificial intelligence that can learn from and mimic large amounts of data to cr...

Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSeg.

Magnetic resonance imaging (MRI) has played a crucial role in fetal neurodevelopmental research. Structural annotations of MR images are an important ...

Network reorganisation reveals somato-motor transition from segregation to integration during tonic pain.

The sustained nature of tonic pain makes it a useful experimental analogue for studying the prolonged neural processing involved in chronic pain. Howe...

Construction of a classification system for long-term care service needs among the elderly based on cluster analysis and machine learning: A multi-center, cross-sectional study in central China.

BACKGROUND: Rapid global aging has led to an increasing demand for long-term care services for the elderly; however, current long-term care systems ar...

Shape matters: Predicting Huntington's disease using progression modelling.

BACKGROUND: Despite evidence of group-level differences in striatal morphometry among persons with Huntington's Disease (PwHD), current models of HD p...

Fast prototyping of memristors for ReRAMs and neuromorphic computing.

The growing demand for energy-efficient computing in artificial intelligence requires novel memory technologies capable of storing and processing info...

Caries Microbiome: time to move from blame to balance.

BACKGROUND: Advances in next-generation sequencing(NGS) and multi-omics approaches reinforced the concept of functional diversity within biofilm commu...

Active guidance in ultrasound bladder scanning using reinforcement learning.

Accurate measurement of bladder volume is essential for diagnosing urinary retention and voiding dysfunction. However, finding optimal view can be cha...

Tuning pH for the Controlled Formation of Ultrasmall Nanoparticles with Direct Cytosolic Access.

Direct cytosolic delivery of nanoparticles offers advantages by circumventing the endocytic pathway, thereby reducing associated intracellular traffic...

Intelligent navigation of potential energy surfaces: leveraging deep reinforcement learning paradigms for accelerated discovery of stable nickel nanoclusters.

The functional properties of nanoclusters are dictated by their atomic-scale structures; however, the efficient discovery of global energy minima on c...

Moving intentions from brains to machines.

Brain-computer interface (BCI) research has achieved remarkable technical progress but remains limited in scope, typically relying on motor and visual...

Better Inputs, Better Learning: A Peptide Embedding Tutorial for Proteomic Mass Spectrometry.

Mass spectrometry proteomics creates complex data representing the peptide/protein contents of biological samples. Various types of machine learning h...

Artificial Intelligence in Snoring Sound Analysis: OSA Detection and Obstruction Site Classification, a Systematic Review.

OBJECTIVE: The aim of the systematic review is to evaluate the application of machine learning (ML) and artificial intelligence (AI) models in the ana...

Preliminary insights into artificial intelligence guided dosing in hypertension and diabetes: challenges and lessons learnt in a pilot feasibility study.

OBJECTIVE: CURATE.AI is an artificial intelligence platform enabling personalised drug dosing. Aims:1) Determine the feasibility of using CURATE.AI in...