Identifying and Reporting Dependent Adult abuse

Machine learning in project analytics: a data-driven framework and case study.

The analytic procedures incorporated to facilitate the delivery of projects are often referred to as project analytics. Existing techniques focus on retrospective reporting and understanding the underlying relationships to make informed decisions. Although machine learning algorithms have been widely used in addressing problems within various contexts (e.g., streamlining the design of construction...

A systematic review of robot-assisted anti-reflux surgery to examine reporting standards.

Robot-assisted anti-reflux surgery (RA-ARS) is increasingly being used to treat refractory gastro-oesophageal reflux disease. The IDEAL (Idea, Development, Exploration, Assessment, Long-term follow up) Collaboration's framework aims to improve the evaluation of surgical innovation, but the extent to which the evolution of RA-ARS has followed this model is unclear. This study aims to evaluate the s...

Quality of reporting of randomised controlled trials of artificial intelligence in healthcare: a systematic review.

OBJECTIVES: The aim of this study was to evaluate the quality of reporting of randomised controlled trials (RCTs) of artificial intelligence (AI) in h...

Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has b...

Human-likeness and attribution of intentionality predict vicarious sense of agency over humanoid robot actions.

Sense of Agency (SoA) is the feeling of being in control of one's actions and their outcomes. In a social context, people can experience a "vicarious"...

Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis.

Machine learning (ML) algorithms are becoming increasingly pervasive in the domains of medical diagnostics and prognostication, afforded by complex de...

Effect of Robot-Assisted Training on Unilateral Spatial Neglect After Stroke: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Several studies have shown that robotic devices can effectively improve motor function in stroke patients through limb activation. However...

Deep learning for automatic brain tumour segmentation on MRI: evaluation of recommended reporting criteria via a reproduction and replication study.

OBJECTIVES: To determine the reproducibility and replicability of studies that develop and validate segmentation methods for brain tumours on MRI and ...

Deep reinforcement learning guided graph neural networks for brain network analysis.

Modern neuroimaging techniques enable us to construct human brains as brain networks or connectomes. Capturing brain networks' structural information ...

Evaluation of an artificial intelligence algorithm for assisting the Paris System in reporting urinary cytology: A pilot study.

BACKGROUND: The Paris System for Reporting Urinary Cytology (TPS) has been shown to improve bladder cancer diagnosis. Advances in artificial intellige...

ALSA: Adversarial Learning of Supervised Attentions for Visual Question Answering.

Visual question answering (VQA) has gained increasing attention in both natural language processing and computer vision. The attention mechanism plays...

Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI.

Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetit...

Motion Feature Aggregation for Video-Based Person Re-Identification.

Most video-based person re-identification (re-id) methods only focus on appearance features but neglect motion features. In fact, motion features can ...

The current status of robotic colorectal surgery training programmes.

Robotic-assisted colorectal surgery (RACS) is steadily increasing in popularity with an annual growth in the number of colorectal procedures undertake...

Comparing neural models for nested and overlapping biomedical event detection.

BACKGROUND: Nested and overlapping events are particularly frequent and informative structures in biomedical event extraction. However, state-of-the-a...

Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast.

Deep learning has been a prevalence in computational chemistry and widely implemented in molecular property predictions. Recently, self-supervised lea...

Utilization of sentiment analysis to assess and compare negative finding reporting in veterinary and human literature.

Publication bias and the decreased publication of trials with negative or non-significant results is a well-recognized problem in human and veterinary...

Learning Cross-Modal Common Representations by Private-Shared Subspaces Separation.

Due to the inconsistent distributions and representations of different modalities (e.g., images and texts), it is very challenging to correlate such h...

Predicting Perceived Reporting Complexity of Abdominopelvic Computed Tomography With Deep Learning.

OBJECTIVE: The purpose of this pilot study was to examine human and automated estimates of reporting complexity for computed tomography (CT) studies o...

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, ...