Frontiers in Artificial Intelligence | New and Recent Articles

As artificial intelligence (AI) becomes deeply embedded in organizational cognition and decision-making, a profound paradox emerges: AI significantly enhances operational efficiency while systematically eroding the generation and retention of innovation drivers. This study introduces the institutional interface as a meso-level analytical lens for examining how specific configurations of AI design…

Artificial intelligence is increasingly embedded in educational processes, yet much of the literature continues to examine individual tools rather than the relationships amongst pedagogy, curriculum, assessment, knowledge validation, institutional authority, and governance. This systematic narrative review examines these relationships whilst explicitly separating evidence-based patterns from conc…

Accurate and efficient automated analysis of Optical Coherence Tomography (OCT) images is critical for large-scale retinal disease screening. However, current deep learning models often fail to simultaneously achieve high classification accuracy, practical computational feasibility, and interpretability. To deal with these problems, this paper presents a deep learning framework on YOLOv11 for eig…

Financial entity-level sentiment analysis aims to identify sentiment polarity toward specific financial entities in financial texts. This task is challenging because a single sentence may contain multiple entities with opposite sentiment orientations, while financial sentiment is often conveyed through domain-specific and implicit cues, increasing the risk of entity confusion. To address these ch…

Somalia’s education system continues to face severe constraints, including weak infrastructure, limited teacher support, and unequal access to learning resources. At the same time, generative artificial intelligence is increasingly entering educational practice through tools that can translate language, support writing, generate explanations, and extend tutoring beyond classroom hours. This Persp…

IntroductionObesity is a critical global health challenge due to its close association with cardiovascular and metabolic risk. At the molecular level, the lipotoxic environment alters the structure, dynamics, and connectivity of the mitochondrial network. Despite advances in cell biology and digital health, there is a lack of lightweight computational tools capable of integrating clinical records…

Accurate forecasting of gold futures prices is very important for investors and analysts due to the highly volatile and nonlinear nature of the commodity markets. This research work develops a hybrid ICA-GRU framework to gold futures price forecasting by developing a hybrid approach of ICA and GRU-based neural networks. The historical daily gold futures price data spanning from 2015 to 2026 were …

Ensuring the safety and dependability of power batteries has become a major concern due to the rapid expansion of electric vehicles (EVs), and fault detection has emerged as an essential approach for guaranteeing system stability. This study develops a Deep Learning (DL)-based defect prediction technique that combines an optimization algorithm and a Context-Aware Recurrent Neural Network with Ada…

Lithium-ion batteries are utilized in electric vehicles (EVs), and accurate predictions of battery state of charge (SOC), state of health (SOH), and remaining useful life (RUL) are needed to ensure reliability, security, and durability of these batteries. This study provides a hybrid deep learning (DL) system, termed as Neural Basis Expansion Variational Ladder Transformer (NBE-VLT), integrating …

IntroductionArtificial Intelligence (AI)-enabled Digital Twins are emerging as advanced cyber-physical technologies that support real-time decision-making, predictive analytics, and operational optimization. However, limited empirical evidence exists on the organizational factors influencing their adoption in hospitality, particularly across countries with different levels of digital maturity and…

BackgroundCardiac involvement in Fabry disease spans structural hypertrophy, mechanical dysfunction, and electrical conduction abnormalities that rarely progress in parallel. Although such discordant longitudinal behavior is commonly encountered in clinical practice, it has not been systematically organized within a coherent longitudinal framework.MethodsWe conducted a retrospective multicenter l…

IntroductionThe rapid expansion of artificial intelligence (AI) in human resource management has substantially reshaped how organizations attract, recruit, develop, evaluate, and retain their workforce. Research examining the combined employee-level effects of AI-enabled digital HRM (AI-DHRM)—through psychological mediating processes and under technology-related boundary conditions—remains sparse…

Automatic cardiac arrhythmia detection using electrocardiogram (ECG) signals is essential for early diagnosis of cardiovascular conditions. Most of the previously existing systems for arrhythmia detection depend on fully supervised learning approaches. In addition to that, since the ECG patient data is centrally stored, it can raise concerns like privacy and security in healthcare environments. T…

Crop recommendation is a vital part of precision agriculture as it helps farmers choose appropriate crops according to the nutrient profile and environmental conditions. This paper presents a crop recommendation framework in which Multi-Layer Perceptron (MLP), XGBoost, and Tab Transformer are first evaluated as baseline prediction models, followed by the proposed Krill Herd Optimization (KHO)-bas…

Background and aimsArtificial intelligence-based computer-aided detection (CADe) systems have been developed to enhance the adenoma detection rate (ADR) during colonoscopy, but their performance is unknown. We primarily aimed to compare the effectiveness of each CADe system with conventional colonoscopy (CC). As a secondary objective, we performed an exploratory comparison among different CADe sy…

Modern clinical epidemiology and artificial intelligence are increasingly driven by an idealized premise: the belief that massive databases and advanced machine learning can redeem causal inference from observational uncertainty. Behind the facade of multi-million-record cohorts, however, a profound epistemological crisis festers, revealing a potentially sick artificial intelligence. Modern analy…

Esophageal squamous cell carcinoma (ESCC) remains a major cause of cancer-related mortality, and prognosis depends strongly on detection at a curable stage. Endoscopy is central to screening and diagnosis, but subtle flat lesions, operator dependence, cognitive fatigue, lesion-location blind spots, and variability in interpretation contribute to missed or delayed diagnosis. Artificial intelligenc…

PurposeWith the growing integration of Artificial Intelligence (AI) into contemporary workplaces, understanding how AI-enabled work systems influence employee wellbeing has become an important concern within HRM research, digital work literature, and future-of-work scholarship.Design/methodology/approachDrawing on the Job Demands–Resources (JD-R) model and Conservation of Resources (COR) theory, …

Online voice-based applications and speech communication have grown as a result of the revolutionary rise of smart gadgets and social media. The rapid advancement of deep learning (DL) has transformed the field of audio processing, enabling smooth human-computer interaction. DL approaches have been used to develop speech-to-text (STT) systems across various languages and topics. These models requ…