Product Alert

Using artificial intelligence to automate meat cut identification from the semimembranosus muscle on beef boning lines.

The identification of different meat cuts for labeling and quality control on production lines is still largely a manual process. As a result, it is a labor-intensive exercise with the potential for not only error but also bacterial cross-contamination. Artificial intelligence is used in many disciplines to identify objects within images, but these approaches usually require a considerable volume ...

Single feature spatio-temporal architecture for EEG Based cognitive load assessment.

The study of electroencephalography (EEG) data for cognitive load analysis plays an important role in identification of stress-inducing tasks. This can be useful in applications such as optimal work allocation, increasing efficiency in the workplace and ensuring safety in difficult work environments. In order for such systems to be realistically deployable, easy acquisition and processing of the d...

Automatic Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue in Non-Contrast Cardiac CT scans.

An Automatic deep learning semantic segmentation (ADLS) using DeepLab-v3-plus technique is proposed for a full and accurate whole heart Epicardial adi...

sEMG-Based Hand Movement Regression by Prediction of Joint Angles With Recurrent Neural Networks.

This work takes a step towards a better biosignal based hand gesture recognition by investigating the strategies for a reliable prediction of hand joi...

DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter.

OBJECTIVE: Research on pharmacovigilance from social media data has focused on mining adverse drug events (ADEs) using annotated datasets, with public...

A comprehensive review of the imbalance classification of protein post-translational modifications.

Post-translational modifications (PTMs) play significant roles in regulating protein structure, activity and function, and they are closely involved i...

A data-driven approach to post-stroke aphasia classification and lesion-based prediction.

Aphasia is an acquired impairment in the production or comprehension of language, typically caused by left hemisphere stroke. The subtyping framework ...

[Robot-assisted nephroureterectomy requiring no robot redocking or patient repositioning: experience from a single center with 62 cases].

To examine a new technique of robot-assisted nephroureterectomy without robot reldocking or patient repositioning. Patients diagnosed as upper tract...

Machine learning-integrated omics for the risk and safety assessment of nanomaterials.

With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessitie...

Open Targets Platform: supporting systematic drug-target identification and prioritisation.

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic targe...

Automated Detection of Enhanced DBS Device Settings.

Continuous deep brain stimulation (DBS) of the ventral striatum (VS) is an effective treatment for severe, treatment-refractory obsessive-compulsive d...

Deep learning for drug-drug interaction extraction from the literature: a review.

Drug-drug interactions (DDIs) are crucial for drug research and pharmacovigilance. These interactions may cause adverse drug effects that threaten pub...

[Establishment and clinical testing of pancreatic cancer Faster R-CNN AI system based on fast regional convolutional neural network].

To investigate the effectiveness of an enhanced CT automatic recognition system based on Faster R-CNN for pancreatic cancer and its clinical value. ...

Wavelet Spectral Deep-training of Convolutional Neural Networks for Accurate Identification of High-Frequency Micro-Scale Spike Transients in the Post-Hypoxic-Ischemic EEG of Preterm Sheep.

Early diagnosis and prognosis of babies with signs of hypoxic-ischemic encephalopathy (HIE) is currently limited and requires reliable prognostic biom...

Wavelet Spectral Time-Frequency Training of Deep Convolutional Neural Networks for Accurate Identification of Micro-Scale Sharp Wave Biomarkers in the Post-Hypoxic-Ischemic EEG of Preterm Sheep.

Neonatal hypoxic-ischemic encephalopathy (HIE) evolves over different phases of time during recovery. Some neuroprotection treatments are only effecti...

Semiautomated Approach for Muscle Weakness Detection in Clinical Texts.

The automated detection of adverse events in medical records might be a cost-effective solution for patient safety management or pharmacovigilance. Ou...

Robotic treatment of the upper limb in chronic stroke and cerebral neuroplasticity: a systematic review.

Stroke is the second cause of mortality and the third cause of long-term disability worldwide. Deficits in upper limb (UL) capacity persist at 6 month...

Hand motion analysis during robot-aided rehabilitation in chronic stroke.

A high percentage of post-stroke patients reports spasticity and no functional use of the upper limb. To adapt the therapy in the most patient-specifi...

Machine Intelligence in Cardiovascular Medicine.

The computer science technology trend called artificial intelligence (AI) is not new. Both machine learning and deep learning AI applications have rec...

Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination.

INTRODUCTION: Identification of adverse events and determination of their seriousness ensures timely detection of potential patient safety concerns. A...