Identifying and Reporting Dependent Adult abuse

Hyper-Mol: Molecular Representation Learning via Fingerprint-Based Hypergraph.

With the development of artificial intelligence (AI) in the field of drug design and discovery, learning informative representations of molecules is becoming crucial for those AI-driven tasks. In recent years, the graph neural networks (GNNs) have emerged as a preferred choice of deep learning architecture and have been successfully applied to molecular representation learning (MRL). Up-to-date MR...

Robotic pelvic side-wall lymph node dissection for rectal cancer: a systematic review of videos and application of the IDEAL 2A framework.

Lateral pelvic lymph node dissection (LPLND) in rectal cancer has gained increasing traction worldwide. Robotic LPLND is an emerging technique. Utilising the IDEAL (idea, development, exploration, assessment and long-term follow-up) framework for surgical innovation, robotic LPLND is currently at the IDEAL 2A stage (development) mainly limited to case reports, case series and videos. A systematic ...

Performance of the Vitek 2 Advanced Expert System (AES) as a Rapid Tool for Reporting Antimicrobial Susceptibility Testing (AST) in from North and Latin America.

This study evaluated the performance of the Vitek 2 Advanced Expert System (AES) confidence level report as a rapid tool for reporting antimicrobial s...

Implementation of Deep-Learning-Based CSI Feedback Reporting on 5G NR-Compliant Link-Level Simulator.

Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for i...

Recommended practices and ethical considerations for natural language processing-assisted observational research: A scoping review.

An increasing number of studies have reported using natural language processing (NLP) to assist observational research by extracting clinical informat...

Artificial intelligence in diagnostic and interventional radiology: Where are we now?

The emergence of massively parallel yet affordable computing devices has been a game changer for research in the field of artificial intelligence (AI)...

Artificial Intelligence Implementation in Healthcare: A Theory-Based Scoping Review of Barriers and Facilitators.

There is a large proliferation of complex data-driven artificial intelligence (AI) applications in many aspects of our daily lives, but their implemen...

Developing a deep learning natural language processing algorithm for automated reporting of adverse drug reactions.

The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an inciden...

Subarchitecture Ensemble Pruning in Neural Architecture Search.

Neural architecture search (NAS) is gaining more and more attention in recent years because of its flexibility and remarkable capability to reduce the...

Unsupervised graph-level representation learning with hierarchical contrasts.

Unsupervised graph-level representation learning has recently shown great potential in a variety of domains, ranging from bioinformatics to social net...

Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system.

OBJECTIVES: To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting...

Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.

Rapid detection of intracranial haemorrhage (ICH) is crucial for assessing patients with neurological symptoms. Prioritising these urgent scans for re...

Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.

Comparing a family structure to a company, one can often think of parents as leaders and adolescents as employees. Stressful family environments and a...

Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis.

Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in practice is critical. Clinical evaluation aims to confirm a...

More refined superbag: Distantly supervised relation extraction with deep clustering.

Distant supervision (DS) can automatically generate annotated data for relation extraction (RE) with knowledge bases and corpora. The existing DS meth...

Using AAEHS-Net as an Attention-Based Auxiliary Extraction and Hybrid Subsampled Network for Semantic Segmentation.

Semantic segmentation based on deep learning has undergone remarkable advancements in recent years. However, due to the neglect of the shallow feature...

Training-Free Deep Generative Networks for Compressed Sensing of Neural Action Potentials.

Energy consumption is an important issue for resource-constrained wireless neural recording applications with limited data bandwidth. Compressed sensi...

Neural Networks for Survival Prediction in Medicine Using Prognostic Factors: A Review and Critical Appraisal.

Survival analysis deals with the expected duration of time until one or more events of interest occur. Time to the event of interest may be unobserved...

An interpretable deep learning model for classifying adaptor protein complexes from sequence information.

Adaptor proteins (APs) are a family of proteins that aids in intracellular membrane trafficking, and their impairments or defects are closely related ...

Marker-Independent Food Identification Enabled by Combing Machine Learning Algorithms with Comprehensive GC × GC/TOF-MS.

Reliable methods are always greatly desired for the practice of food inspection. Currently, most food inspection techniques are mainly dependent on th...