Academic Articles & Research Papers

Artificial Intelligence, Automation and Work

We summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment.Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace la...

An automated deep learning framework for brain tumor classification using MRI imagery

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

The Effects of Large Language Models on the Generation of Multiple-choice Questions in Medical Education: A Scoping Review

Background: Constructing high-quality multiple-choice questions (MCQs) is critical yet resource-intensive in medical education. Large language models (LLMs), such as ChatGPT, have become promising tools for generating MCQs in medical educat...

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

Discussion on Artificial Intelligence Safety and Ethical Issues

As artificial intelligence (AI) is increasingly integrated into society, people are relying on it more and more, and higher requirements are put forward for the safety and ethical standards of AI. This article explores the development of ar...

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

Artificial Intelligence-Driven Salivary Biomarkers for Detection and Risk Stratification of Oral Potentially Malignant Disorders and OSCC: A Protocol for a Systematic Review

Objective This systematic review protocol aims to synthesize evidence on artificial intelligence-driven analysis of salivary biomarkers for the detection, risk stratification and differentiation of OPMDs and OSCC, with particular attention ...

Deep nested U-structure network with frequency attention for building semantic segmentation

Abstract The automated segmentation of buildings from remotely sensed imagery has undergone extensive research and application across various industrial domains. Despite this, several challenges persist, including incomplete internal extrac...

AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction

This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function...

Neural Networks and Artificial’s Intelligence’s Algorithms in the Tasks of Diagnostics Foreign Bodies

The paper considers a device in which information about the presence of a foreign body a fragment in a wound is obtained using a special compact sensor: a mechanical elastic flexible rod, which is placed in a protective soft tube and connec...

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

Colonoscopy Quality and Strategies for Improvement

Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscopist performance, which can vary. Missed lesions during colonoscopy can lead to post-colono...

From AI Readiness to Human Readiness: A Human-Centered Framework for AI Adoption in SMEs

Artificial intelligence (AI) is transforming organizations across all sectors, yet many AI initiatives fail despite significant technological investments. Existing research has primarily explained AI adoption through technological, organiza...

Sparsity Increases Uncertainty Estimation in Deep Ensemble

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavi...

Convergence of Artificial Intelligence and Wearables in Strength Training and Performance Monitoring: A Scoping Review

Background: Strength training (ST) is essential for enhancing athletic performance and reducing injury risk, yet traditional monitoring relies heavily on subjective assessment, limiting objective and individualized evaluation. Objective: Th...

Extracting behavioral patterns of people in crowdfunding projects using artificial intelligence and identify key investors

Crowdfunding as a new method has an important contribution to projects, especially for small and medium-sized businesses. Despite the many years of activity of crowdfunding platforms in Iran, the scale of projects and the volume of capital ...

A Comparative Analysis of Supervised and Unsupervised Models for Detecting Attacks on the Intrusion Detection Systems

Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and ...

Bayesian Artificial Intelligence

As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in m...

A meta-analysis of the relation between math anxiety and math achievement.

Meta-analyses from the 1990s have previously established a significant, small-to-moderate, and negative correlation between math achievement and math anxiety. Since these publications, research has continued to investigate this relation wit...

Counteracting the overestimation of effect size in mass-univariate brain-wide association studies using cross-validation.