Staffing & Scheduling

Artificial Intelligence Training in Canadian Dermatology to Increase Dermatologists Engagement and Enhance Medical Practice.

Achieving Online Regression Performance of LSTMs With Simple RNNs.

Recurrent neural networks (RNNs) are widely used for online regression due to their ability to gener...

Efficacy and Safety of the "Trisection Method" Training System for Robot-Assisted Radical Cystectomy at a Single Institution in Japan.

To maintain a surgeon's concentration, reduce fatigue, and train young surgeons, surgical procedures...

Simple add-on robotic traction device to the conventional endoscope: Will it be an efficient and safe tool for novice training on endoscopic submucosal dissection?

A large-scale neural network training framework for generalized estimation of single-trial population dynamics.

Achieving state-of-the-art performance with deep neural population dynamics models requires extensiv...

Technical note: Phantom-based training framework for convolutional neural network CT noise reduction.

BACKGROUND: Deep artificial neural networks such as convolutional neural networks (CNNs) have been s...

Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.

Although deep learning (DL) has demonstrated impressive diagnostic performance for a variety of comp...

AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics.

Machine learning and in particular deep learning (DL) are increasingly important in mass spectrometr...

Ultrasound-enhanced catalytic degradation of simulated dye wastewater using waste printed circuit boards: catalytic performance and artificial neuron network-based simulation.

Recent developments of heterogeneous advanced oxidation for refractory organic contaminants and cata...

An Orchestration Platform that Puts Radiologists in the Driver's Seat of AI Innovation: a Methodological Approach.

Current AI-driven research in radiology requires resources and expertise that are often inaccessible...

Influence of Insufficient Dataset Augmentation on IoU and Detection Threshold in CNN Training for Object Detection on Aerial Images.

The objects and events detection tasks are being performed progressively often by robotic systems li...

[Automation and the use of robots in the pathology laboratory : A journey through time and a consideration of efficiency].

In the past 20 years, numerous technical innovations were introduced to the histopathology laborator...

Transfer of open and laparoscopic skills to robotic surgery: a systematic review.

Due to its advantages over open surgery and conventional laparoscopy, uptake of robot-assisted surge...

Short-term outcomes of robot-assisted versus conventional laparoscopic surgery for mid and low rectal cancer after neoadjuvant chemoradiotherapy: a propensity score-matched analysis.

The benefits of robot-assisted laparoscopic surgery (RALS) for rectal cancer remain controversial. O...

Systematic review of academic robotic surgery curricula.

The use of robotic surgery has increased exponentially in the United States. Despite this uptick in ...

Multidisciplinary perceptions on robotic surgical training: the robot is a stimulus for surgical education change.

BACKGROUND: It is unclear how to best establish successful robotic training programs or if subspecia...

Unsupervised Learning Composite Network to Reduce Training Cost of Deep Learning Model for Colorectal Cancer Diagnosis.

Deep learning facilitates complex medical data analysis and is increasingly being explored in colore...

Appropriate Learning Rates of Adaptive Learning Rate Optimization Algorithms for Training Deep Neural Networks.

This article deals with nonconvex stochastic optimization problems in deep learning. Appropriate lea...

Computational Intelligence Based Recurrent Neural Network for Identification Deceptive Review in the E-Commerce Domain.

Most consumers depend on online reviews posted on e-commerce websites when determining whether or no...

Direct Evaluation of Treatment Response in Brain Metastatic Disease with Deep Neuroevolution.

Cancer centers have an urgent and unmet clinical and research need for AI that can guide patient man...

On the usability of synthetic data for improving the robustness of deep learning-based segmentation of cardiac magnetic resonance images.

Deep learning-based segmentation methods provide an effective and automated way for assessing the st...