Work Force

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders.

BACKGROUND: In clinical practice, therapists choose the amount of assistance for robot-assisted trai...

[Do artificial intelligence systems reason in the same way as clinicians when making diagnoses?].

Clinical reasoning is at the heart of physicians' competence, as it allows them to make diagnoses. H...

Training high-performance and large-scale deep neural networks with full 8-bit integers.

Deep neural network (DNN) quantization converting floating-point (FP) data in the network to integer...

A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration.

To achieve accurate and fast deformable image registration (DIR) for pulmonary CT, we proposed a Mul...

Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach.

Cardiac magnetic resonance imaging (MRI) provides a wealth of imaging biomarkers for cardiovascular ...

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

BACKGROUND: An increasing volume of prostate biopsies and a worldwide shortage of urological patholo...

Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data.

Prediction models of post-liver transplant mortality are crucial so that donor organs are not alloca...

Reliability, validity and discriminant ability of a robotic device for finger training in patients with subacute stroke.

BACKGROUND: The majority of stroke survivors experiences significant hand impairments, as weakness a...

Stress among Portuguese Medical Students: the EuStress Solution.

There has been an increasing attention to the study of stress. Particularly, college students often ...

Learning efficient haptic shape exploration with a rigid tactile sensor array.

Haptic exploration is a key skill for both robots and humans to discriminate and handle unknown obje...

Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research.

OBJECTIVE: The speed of the diagnosis process is vital in pursuing the trial of curing cancer. Durin...

Neural Network Ensembles for Sensor-Based Human Activity Recognition Within Smart Environments.

In this paper, we focus on data-driven approaches to human activity recognition (HAR). Data-driven a...

Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose-volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy.

PURPOSE: We propose a novel domain-specific loss, which is a differentiable loss function based on t...

Highest ambulatory speed using Lokomat gait training for individuals with a motor-complete spinal cord injury: a clinical pilot study.

BACKGROUND: Motor impairment and loss of ambulatory function are major consequences of a spinal cord...

The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses.

While prosthetic fitting after upper-limb loss allows for restoration of motor functions, it deprive...

Re-examining physician-scientist training through the prism of the discovery-invention cycle.

The training of physician-scientists lies at the heart of future medical research. In this commentar...

An Effective MR-Guided CT Network Training for Segmenting Prostate in CT Images.

Segmentation of prostate in medical imaging data (e.g., CT, MRI, TRUS) is often considered as a crit...

Training neural networks to encode symbols enables combinatorial generalization.

Combinatorial generalization-the ability to understand and produce novel combinations of already fam...

Improving gesture-based interaction between an assistive bathing robot and older adults via user training on the gestural commands.

BACKGROUND: Gesture-based human-robot interaction (HRI) depends on the technical performance of the ...

Multi-objective ensemble deep learning using electronic health records to predict outcomes after lung cancer radiotherapy.

Accurately predicting treatment outcome is crucial for creating personalized treatment plans and fol...

Editorial for "Deep-Learning-Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size".