Work Force

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 ...

Impact of robotic single and dual console systems in the training of minimally invasive gynecology surgery (MIGS) fellows.

The advantages of dual console use in robotic surgical education have not been described. The aims o...

Granularity and Entropy of Intuitionistic Fuzzy Information and Their Applications.

A granular structure of intuitionistic fuzzy (IF) information presents simultaneously the similarity...

Mini-batch optimization enables training of ODE models on large-scale datasets.

Quantitative dynamic models are widely used to study cellular signal processing. A critical step in ...

An Efficient Deep Learning Approach to Automatic Glaucoma Detection Using Optic Disc and Optic Cup Localization.

Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and caused comp...

Dynamic training of a novelty classifier algorithm for real-time detection of early seizure onset.

OBJECTIVE: To develop an adaptive framework for seizure detection in real-time that is practical to ...

Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach.

A pivotal topic in agriculture and food monitoring is the assessment of the quality and ripeness of ...

Assessment of a hybrid decision support system using machine learning with artificial intelligence to safely rule out prescriptions from medication review in daily practice.

Background Medication review is time-consuming and not exhaustive in most French hospitals. We routi...

Tungsten oxide polymorphs and their multifunctional applications.

Owing to the natural abundance, easy availability, high stability, non-stoichiometry, and chemical d...

Force Myography-Based Human Robot Interactions via Deep Domain Adaptation and Generalization.

Estimating applied force using force myography (FMG) technique can be effective in human-robot inter...

Domain generalization on medical imaging classification using episodic training with task augmentation.

Medical imaging datasets usually exhibit domain shift due to the variations of scanner vendors, imag...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial an...

When unsupervised training benefits category learning.

Humans continuously categorise inputs, but only rarely receive explicit feedback as to whether or no...

Diversity-Sensitive Generative Adversarial Network for Terrain Mapping Under Limited Human Intervention.

In a collaborative air-ground robotic system, the large-scale terrain mapping using aerial images is...

A Novel Training and Collaboration Integrated Framework for Human-Agent Teleoperation.

Human operators have the trend of increasing physical and mental workloads when performing teleopera...

Training a deep learning model for single-cell segmentation without manual annotation.

Advances in the artificial neural network have made machine learning techniques increasingly more im...

Predicting anesthetic infusion events using machine learning.

Recently, research has been conducted to automatically control anesthesia using machine learning, wi...