Staffing & Scheduling

Cubature Kalman Filter Based Training of Hybrid Differential Equation Recurrent Neural Network Physiological Dynamic Models.

Modeling biological dynamical systems is challenging due to the interdependence of different system ...

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance...

Dawn of artificial intelligence - Enable digital Pathology in Pakistan: A paradigm shift.

Optimization of Radiology Workflow with Artificial Intelligence.

The potential of artificial intelligence (AI) in radiology goes far beyond image analysis. AI can be...

Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training.

In this paper, we introduce the , a nonconvex, yet analytically tractable, optimization program, in ...

Social Work and Artificial Intelligence: Into the Matrix.

Preventing dataset shift from breaking machine-learning biomarkers.

Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedic...

Training for object recognition with increasing spatial frequency: A comparison of deep learning with human vision.

The ontogenetic development of human vision and the real-time neural processing of visual input exhi...

Diverse Deep Neural Networks All Predict Human Inferior Temporal Cortex Well, After Training and Fitting.

Deep neural networks (DNNs) trained on object recognition provide the best current models of high-le...

Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.

Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique abil...

The Clinician and Dataset Shift in Artificial Intelligence.

Robotics in Spine Surgery and Spine Surgery Training.

The increasing interest and advancements in robotic spine surgery parallels a growing emphasis on ma...

Comment on: Shortening surgical training through robotics: randomized clinical trial of laparoscopic versus robotic surgical learning curves.

Exploiting the power of information in medical education.

The explosion of medical information demands a thorough reconsideration of medical education, includ...

AI-ssessment: Towards Assessment As a Sociotechnical System for Learning.

Two decades ago, the advent of competency-based medical education (CBME) marked a paradigm shift in ...

Machine Learning: The Next Paradigm Shift in Medical Education.

Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinica...

Federated learning improves site performance in multicenter deep learning without data sharing.

OBJECTIVE: To demonstrate enabling multi-institutional training without centralizing or sharing the ...

Skip-Connected Self-Recurrent Spiking Neural Networks With Joint Intrinsic Parameter and Synaptic Weight Training.

As an important class of spiking neural networks (SNNs), recurrent spiking neural networks (RSNNs) p...

Performance and educational training of radiographers in lung nodule or mass detection: Retrospective comparison with different deep learning algorithms.

The aim of this investigation was to compare the diagnostic performance of radiographers and deep le...

Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity.

Semi-supervised learning has always been a hot topic in machine learning. It uses a large number of ...

Performance of SURF and SIFT Keypoints for the Automated Differentiation of Abnormality in Chest Radiographs.

In this work, automated abnormality detection using keypoint information from Speeded-Up Robust feat...