Staffing & Scheduling

AI firms must play fair when they use academic data in training.

Frontoparietal and salience network synchronizations during nonsymbolic magnitude processing predict brain age and mathematical performance in youth.

The development and refinement of functional brain circuits crucial to human cognition is a continuo...

EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.

Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology fo...

Exploiting Metabolic Defects in Glioma with Nanoparticle-Encapsulated NAMPT Inhibitors.

The treatment of primary central nervous system tumors is challenging due to the blood-brain barrier...

GR-pKa: a message-passing neural network with retention mechanism for pKa prediction.

During the drug discovery and design process, the acid-base dissociation constant (pKa) of a molecul...

Staff Management with AI: Predicting the Nursing Workload.

The effective management of human resources in nursing fundamental to ensuring high-quality care. Th...

Nursing Education and Artificial Intelligence.

The American Association of Colleges of Nursing (AACN) is shifting the nursing education paradigm to...

Identifying and training deep learning neural networks on biomedical-related datasets.

This manuscript describes the development of a resources module that is part of a learning platform ...

Practical applications of artificial intelligence in dermatology residency training.

Structure Preserving Cycle-Gan for Unsupervised Medical Image Domain Adaptation.

The presence of domain shift in medical imaging is a common issue, which can greatly impact the perf...

Biosignal-based Control of a Robotic Gait Training Lifter.

In this paper, we present a robotic walker that aims to encourage the patient's voluntary movement b...

Changes in pressure of strap while walking in a robotic gait training system.

Exoskeletons have been developed and widely used for medical, industrial, military applications. Sin...

Enhancement of Functional Connectivity in Frontal-Parietal Regions After BCI-Actuated Supernumerary Robotic Finger Training.

The supernumerary robotic finger (SRF) can expand human hand abilities to achieve motor augmentation...

Feature Imitating Networks Enhance the Performance, Reliability and Speed of Deep Learning on Biomedical Image Processing Tasks.

Feature-Imitating-Networks (FINs) are neural networks that are first trained to approximate closed-f...

The Effects of Robotic Exoskeleton Gait Training on Improving Walking Adaptability in Persons with MS.

The goal of the present pilot investigation is to examine the effects of 8 weeks of supervised, over...

Predicting Hemodynamic and Pulmonary Decompensation with Deep Neural Networks: Performance and Explainability.

Predicting the deterioration of patients' hemodynamic and pulmonary decompensation state while being...

Automated Assessment of Simulated Laparoscopic Surgical Performance using 3DCNN.

Artificial intelligence & Computer vision have the potential to improve surgical training, especiall...

Multi-Scale Self-Supervised Consistency Training for Trustworthy Medical Imaging Classification.

Modern neural network models have demonstrated exceptional classification capabilities comparable to...

Multidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.

Stroke involves heterogeneity in injury and ongoing endogenous recovery, which are seldom stratified...

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning.

Common artefacts such as baseline drift, rescaling, and noise critically limit the performance of ma...

Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability.

Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucia...