Practice Management

Staffing & Scheduling

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

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An study of lipase inhibitory peptides obtained from de-oiled rice bran.

De-oiled rice bran (DORB) is a potentially useful by-product of the rice bran oil industry. DORB may...

Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size...

Domain Generalization in Biosignal Classification.

OBJECTIVE: When training machine learning models, we often assume that the training data and evaluat...

Designing a hybrid dimension reduction for improving the performance of Amharic news document classification.

The volume of Amharic digital documents has grown rapidly in recent years. As a result, automatic do...

Deep learning neural network tools for proteomics.

Mass-spectrometry-based proteomics enables quantitative analysis of thousands of human proteins. How...

Role of deep learning in brain tumor detection and classification (2015 to 2020): A review.

During the last decade, computer vision and machine learning have revolutionized the world in every ...

Current and emerging artificial intelligence applications for pediatric interventional radiology.

Artificial intelligence in medicine can help improve the accuracy and efficiency of diagnostics, sel...

CancerSiamese: one-shot learning for predicting primary and metastatic tumor types unseen during model training.

BACKGROUND: The state-of-the-art deep learning based cancer type prediction can only predict cancer ...

Martial Arts Routine Training Method Based on Artificial Intelligence and Big Data of Lactate Measurement.

As a traditional Chinese sport, competitive martial arts routines have a long history. The competiti...

Diagnostic accuracy of current machine learning classifiers for age-related macular degeneration: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: The objective of this study was to systematically review and meta-analyze ...

Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews.

Digital data sources have become ubiquitous in modern culture in the era of digital technology but ...

Surgical training fit for the future: the need for a change.

Postgraduate training in surgical specialties is one of the longest training programmes in the medic...

From the Laboratory to the Field: IMU-Based Shot and Pass Detection in Football Training and Game Scenarios Using Deep Learning.

The applicability of sensor-based human activity recognition in sports has been repeatedly shown for...

Performance Assessment of Certain Machine Learning Models for Predicting the Major Depressive Disorder among IT Professionals during Pandemic times.

Major depressive disorder (MDD) is the most common mental disorder in the present day as all individ...

Computational Logistics for Container Terminal Handling Systems with Deep Learning.

Container terminals are playing an increasingly important role in the global logistics network; howe...

A deep neural network-based approach for prediction of mutagenicity of compounds.

We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost...

Neuroevolution-Based Adaptive Antenna Array Beamforming Scheme to Improve the V2V Communication Performance at Intersections.

The opportunistic exchange of information between vehicles can significantly contribute to reducing ...

Robotic General Surgery Resident Training Curriculum: A Pilot Experience.

BACKGROUND: The purpose of this study was to report the impact of a pilot robotic general surgery re...

Ground-truth-free deep learning for artefacts reduction in 2D radial cardiac cine MRI using a synthetically generated dataset.

In this work, we consider the task of image reconstruction in 2D radial cardiac cine MRI using deep ...

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