Practice Management

Staffing & Scheduling

Latest AI and machine learning research in staffing & scheduling for healthcare professionals.

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MolGraph: a Python package for the implementation of molecular graphs and graph neural networks with TensorFlow and Keras.

Molecular machine learning (ML) has proven important for tackling various molecular problems, such a...

MLVICX: Multi-Level Variance-Covariance Exploration for Chest X-Ray Self-Supervised Representation Learning.

Self-supervised learning (SSL) reduces the need for manual annotation in deep learning models for me...

Self-Supervised Pre-Training via Multi-View Graph Information Bottleneck for Molecular Property Prediction.

Molecular representation learning has remarkably accelerated the development of drug analysis and di...

tDKI-Net: A Joint q-t Space Learning Network for Diffusion-Time-Dependent Kurtosis Imaging.

Time-dependent diffusion magnetic resonance imaging (TDDMRI) is useful for the non-invasive characte...

Comparing effects of wearable robot-assisted gait training on functional changes and neuroplasticity: A preliminary study.

Robot-assisted gait training (RAGT) is a promising technique for improving the gait ability of elder...

Data-dependent stability analysis of adversarial training.

Stability analysis is an essential aspect of studying the generalization ability of deep learning, a...

Self-supervised learning via VICReg enables training of EMG pattern recognition using continuous data with unclear labels.

In this study, we investigate the application of self-supervised learning via pre-trained Long Short...

Training humans to supplement a machine learning system: The role of guides in a digital mental health intervention.

Machine learning (ML) is increasingly prevalent in mental health care, with contemporary initiatives...

Effects of Robot-Assisted Gait Training on Balance and Fear of Falling in Patients With Stroke: A Randomized Controlled Clinical Trial.

OBJECTIVE: The aim of this study was compare the effects of combined training, which included robot-...

On the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training: an eye-tracking and HD-EEG study.

BACKGROUND: Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor...

Are more data always better? - Machine learning forecasting of algae based on long-term observations.

Bloom-forming algae present a unique challenge to water managers as they can significantly impair pr...

Using deep learning and word embeddings for predicting human agreeableness behavior.

The latest advancements of deep learning have resulted in a new era of natural language processing. ...

Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).

PURPOSE: Coronary CT angiography (CCTA) is well established for the diagnostic evaluation and progno...

Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to- Aberration Approach.

One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It...

Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis.

Large amounts of fMRI data are essential to building generalized predictive models for brain disease...

Predefined-Time Convergent Kinematic Control of Robotic Manipulators With Unknown Models Based on Hybrid Neural Dynamics and Human Behaviors.

This article proposes a model-free kinematic control method with predefined-time convergence for rob...

A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training.

Brain-computer interfaces (BCIs) provide a direct pathway from the brain to external devices and hav...

Impact of an AI-based laparoscopic cholecystectomy coaching program on the surgical performance: a randomized controlled trial.

BACKGROUND: Laparoscopic cholecystectomy (LC) is the gold standard for treating symptomatic gallston...

Assessing the performance of machine learning algorithms for analyzing land use changes in the Hyrcanian forests of Iran.

Land use changes are of critical importance in understanding and managing environmental sustainabili...

Predicting the time to get back to work using statistical models and machine learning approaches.

BACKGROUND: Whether machine learning approaches are superior to classical statistical models for sur...

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