Surveys

Design of an Interactive Exercise and Leisure System for the Elderly Integrating Artificial Intelligence and Motion-Sensing Technology.

In response to the global trend of population aging, the issue of providing elderly individuals suitable leisure and entertainment has become increasingly important. In this study, it aims to utilize artificial intelligence (AI) technology to offer the elderly with a healthy and enjoyable exercise and leisure experience. A human-machine interactive system is designed using computer vision, a subfi...

Understanding and predicting animal movements and distributions in the Anthropocene.

Predicting animal movements and spatial distributions is crucial for our comprehension of ecological processes and provides key evidence for conserving and managing populations, species and ecosystems. Notwithstanding considerable progress in movement ecology in recent decades, developing robust predictions for rapidly changing environments remains challenging. To accurately predict the effects of...

Photoplethysmography-based HRV analysis and machine learning for real-time stress quantification in mental health applications.

Prolonged exposure to high-stress environments can lead to mental illnesses such as anxiety disorders, depression, and posttraumatic stress disorder. ...

Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.

Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurol...

Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm.

In the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis t...

AI Chatbots as Sources of STD Information: A Study on Reliability and Readability.

BACKGROUND: Artificial intelligence (AI) chatbots are increasingly used for medical inquiries, including sensitive topics like sexually transmitted di...

Integrative Multi-Omics and Routine Blood Analysis Using Deep Learning: Cost-Effective Early Prediction of Chronic Disease Risks.

Chronic noncommunicable diseases (NCDS) are often characterized by gradual onset and slow progression, but the difficulty in early prediction remains ...

A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.

BACKGROUND: In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social medi...

Understanding patterns of loneliness in older long-term care users using natural language processing with free text case notes.

Loneliness and social isolation are distressing for individuals and predictors of mortality, yet data on their impact on publicly funded long-term car...

Identifying the Most Critical Predictors of Workplace Violence Experienced by Junior Nurses: An Interpretable Machine Learning Perspective.

Workplace violence, defined as any disruptive behavior or threat to employees, seriously threatens junior nurses. Compared with senior nurses, junior...

Patient-specific MRI super-resolution via implicit neural representations and knowledge transfer.

Magnetic resonance imaging (MRI) is a non-invasive imaging technique that provides high soft tissue contrast, playing a vital role in disease diagnosi...

Leveraging Artificial Intelligence to Linguistically Compare Test Translations: A Methodological Introduction and Demonstration.

The validity and utility of translated instruments (psychological measures) depend on the quality of their translation, and differences in key linguis...

The NERVE-ML (neural engineering reproducibility and validity essentials for machine learning) checklist: ensuring machine learning advances neural engineering.

Machine learning's (MLs) ability to capture intricate patterns makes it vital in neural engineering research. With its increasing use, ensuring the va...

Deep neural networks excel in COVID-19 disease severity prediction-a meta-regression analysis.

COVID-19 is a disease in which early prognosis of severity is critical for desired patient outcomes and for the management of limited resources like i...

Hybrid CNN and random forest model with late fusion for detection of autism spectrum disorder in Toddlers.

Accurate and early diagnosis of Autism Spectrum Disorder (ASD) in toddlers is crucial for effective intervention. Traditional models have shown limite...

Psychometric properties and Turkish adaptation of the artificial intelligence attitude scale (AIAS-4): evidence for construct validity.

Artificial intelligence (AI) attitude scales can be used to better evaluate the benefit and drawback cons of AI. This article consists of two differen...

Artificial Intelligence and Qualitative Analysis of Emergency Department Telemental Health Care Implementation Survey.

: Implementation of telemental health care in emergency departments (EDs) in the United States (U.S.) has been increasing. Artificial intelligence (AI...

Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be proc...

Critical scenarios adversarial generation method for intelligent vehicles testing based on hierarchical reinforcement architecture.

The widespread deployment of intelligent vehicles necessitates comprehensive testing across diverse driving scenarios. A significant challenge is gene...

CLIP in medical imaging: A survey.

Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision model...