Surveys

Predictive roles of cognitive biases in health anxiety: A machine learning approach.

Prior work suggests that cognitive biases may contribute to health anxiety. Yet there is little research investigating how biased attention, interpretation, and memory for health threats are collectively associated with health anxiety, as well as the relative importance of these cognitive processes in predicting health anxiety. This study aimed to build a prediction model for health anxiety with m...

Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage classification, but trust and reliability issues have hampered its adoption in clinical applications. Estimating uncertainty is a crucial factor in enh...

Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

The purpose of this study was to test whether a machine learning model can accurately predict VO across different exercise intensities by combining mu...

Signatures of Bayesian inference emerge from energy-efficient synapses.

Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechani...

Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images.

Deep learning shows promise in autosegmentation of head and neck cancer (HNC) primary tumours (GTV-T) and nodal metastases (GTV-N). However, errors su...

Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care.

For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essent...

Scoping review on natural language processing applications in counselling and psychotherapy.

Recent years have witnessed some rapid and tremendous progress in natural language processing (NLP) techniques that are used to analyse text data. Thi...

Single-center outcomes of artificial intelligence in management of pulmonary embolism and pulmonary embolism response team activation.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites treatment. The use of artificial intelligence (AI)...

The real ethical issues with AI for clinical psychiatry.

This article explores the ethical issues arising from ordinary AI applications currently used in mental health care, rather than speculative future sc...

Automated Detection of In-Home Activities with Ultra-Wideband Sensors.

As Canada's population of older adults rises, the need for aging-in-place solutions is growing due to the declining quality of long-term-care homes an...

Uncertainty quantification via localized gradients for deep learning-based medical image assessments.

Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep...

Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.

The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of...

The Application of Robotics in Cardiac Rehabilitation: A Systematic Review.

: Robotics is commonly used in the rehabilitation of neuro-musculoskeletal injuries and diseases. While in these conditions, robotics has clear benefi...

Ethical Implications of Artificial Intelligence in Gastroenterology: The Co-pilot or the Captain?

Though artificial intelligence (AI) is being widely implemented in gastroenterology (GI) and hepatology and has the potential to be paradigm shifting ...

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review.

The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound imaging in gynecology oncology. Web of Science, Pu...

Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks.

Assessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for animal model validation and drug development. How...

Validity of zinc oxide nanoparticles biosynthesized in food wastes extract in treating real samples of printing ink wastewater; prediction models using feed-forward neural network (FFNN).

In the present study, biosynthesized ZnO nanoparticles in food wastewater extract (FWEZnO NPs) was used in the photocatalytic degradation of real samp...

Multicenter validation study for automated left ventricular ejection fraction assessment using a handheld ultrasound with artificial intelligence.

We sought to validate the ability of a novel handheld ultrasound device with an artificial intelligence program (AI-POCUS) that automatically assesses...

Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects.

Although artificial intelligence (AI) methods hold promise for medical imaging-based prediction tasks, their integration into medical practice may pre...

Measuring Vertical Jump Height With Artificial Intelligence Through a Cell Phone: A Validity and Reliability Report.

Erik, HT, Onn, SW, and Montalvo, S. Vertical jump height with artificial intelligence through a cell phone: a validity and reliability report. J Stren...