Work Force

COVID-19 Detection Based on Lung Ct Scan Using Deep Learning Techniques.

SARS-CoV-2 is a novel virus, responsible for causing the COVID-19 pandemic that has emerged as a pan...

Detecting Presence of PTSD Using Sentiment Analysis From Text Data.

Rates of Post-traumatic stress disorder (PTSD) have risen significantly due to the COVID-19 pandemic...

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applicatio...

Walking improvement in chronic incomplete spinal cord injury with exoskeleton robotic training (WISE): a randomized controlled trial.

STUDY DESIGN: Clinical trial.

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and ma...

Robot-assisted distal training improves upper limb dexterity and function after stroke: a systematic review and meta-regression.

INTRODUCTION: Stroke is one of the top 10 causes of death worldwide, and more than half of stroke pa...

Effects of Balance Exercise Assist Robot training for patients with hemiparetic stroke: a randomized controlled trial.

BACKGROUND: Robot-assisted rehabilitation for patients with stroke is promising. However, it is uncl...

Motor Ability Evaluation of the Upper Extremity with Point-To-Point Training Movement Based on End-Effector Robot-Assisted Training System.

Assessment is critical during the procedure of stroke rehabilitation. However, traditional assessmen...

Deep Learning for Instrumented Ultrasonic Tracking: From Synthetic Training Data to In Vivo Application.

Instrumented ultrasonic tracking is used to improve needle localization during ultrasound guidance o...

A gradient-based automatic optimization CNN framework for EEG state recognition.

. The electroencephalogram (EEG) signal, as a data carrier that can contain a large amount of inform...

Performance change with the number of training data: A case study on the binary classification of COVID-19 chest X-ray by using convolutional neural networks.

One of the features of artificial intelligence/machine learning-based medical devices resides in the...

A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.

Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in th...

Automatic Placenta Localization From Ultrasound Imaging in a Resource-Limited Setting Using a Predefined Ultrasound Acquisition Protocol and Deep Learning.

Placenta localization from obstetric 2-D ultrasound (US) imaging is unattainable for many pregnant w...

Semisupervised Training of a Brain MRI Tumor Detection Model Using Mined Annotations.

Background Artificial intelligence (AI) applications for cancer imaging conceptually begin with auto...

A Comprehensive Survey on Nanophotonic Neural Networks: Architectures, Training Methods, Optimization, and Activations Functions.

In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have...

Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes.

Facial expressions are an auxiliary embodiment of information conveyed in the communication between ...

Functional Diversity of Primed Platelets-Powered by Machine Learning.

Transfer inhibitory potency prediction to binary classification: A model only needs a small training set.

One of the most laborious for drug discovery is to select compounds from a library for experimental ...

Mix-and-Interpolate: A Training Strategy to Deal With Source-Biased Medical Data.

Till March 31st, 2021, the coronavirus disease 2019 (COVID-19) had reportedly infected more than 127...

Comparative effects of EMG-driven robot-assisted therapy versus task-oriented training on motor and daily function in patients with stroke: a randomized cross-over trial.

BACKGROUND: Robot-assisted hand training has shown positive effects on promoting neuromuscular contr...

Semi-supervised learning for medical image classification using imbalanced training data.

BACKGROUND AND OBJECTIVE: Medical image classification is often challenging for two reasons: a lack ...