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Bridging the Education–Employment Gap in Europe: An AI-Driven Approach to Skill Matching

Ramón Sanguino, Nilgün Çağlarırmak Uslu, Pınar Karahan-Dursun, Caner Özdemir et al. • World (2025)

Education–employment mismatch represents a persistent structural issue across Europe, especially among young people. In line with the digital transformation, green transformation and population aging, new jobs are emerging every day, and so...

DOAJ Open Access (DOAJ) DOI: 10.3390/world6040143

Artificial intelligence: A powerful paradigm for scientific research

Yongjun Xu, Xin Liu, Xin Cao, Changping Huang et al. • The Innovation (2021)

Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day li...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.xinn.2021.100179 PMC: 8633405

Harnessing Machine Learning for Procedural Content Generation in Gaming: A Comprehensive Review

Shaqayeq Saffari, Morteza Dorrigiv, Farzin Yaghmaee • Journal of Artificial Intelligence and Data Mining (2024)

Procedural Content Generation (PCG) through automated and algorithmic content generation is an active research field in the gaming industry. Recently, Machine Learning (ML) approaches have played a pivotal role in advancing this area. While...

DOAJ Open Access (DOAJ) DOI: 10.22044/jadm.2025.15016.2603

Assessing carbon and economic loss from oak decline in Iran’s Zagros forests using Sentinel-2 and machine learning

Saied Pirasteh, Zohreh Bazvand, Naseh Miri, Zhaoxi Fang et al. • Geo-spatial Information Science (2026)

Over recent decades, the decline of oak trees, which has emerged as the most significant challenge to the Zagros forests (ZFs), poses serious threats to carbon storage (CS) and economic valuation, jeopardizing the ecological and economic su...

DOAJ Open Access (DOAJ) DOI: 10.1080/10095020.2026.2682739

Binaural Beat Stimulation Enhances Cognitive Function in Alzheimer’s Disease via Temporal Lobe Activation: An sLORETA Study

Muhammad Danish Mujib, Nayab Mubashir, Ahmad Zahid Rao, Nisha Nasir et al. • Biomedicines (2026)

Background: The global prevalence of Alzheimer’s disease (AD) has reached 55.2 million. AD is characterized by progressive deterioration in cognition and working memory (WM), which are essential for attention, reasoning, and learning. These...

DOAJ Open Access (DOAJ) DOI: 10.3390/biomedicines14030540

The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

Yuri Yin‐Moe Aung, David Wong, Daniel Shu Wei Ting • British Medical Bulletin (2021)

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and...

OPENALEX DOI: https://doi.org/10.1093/bmb/ldab016

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

Ebtisam AlJalaud, Manar Hosny • Mathematics (2024)

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

DOAJ Open Access (DOAJ) DOI: 10.3390/math12233727

A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, Salim Nasar Faraj Mursal et al. • IEEE Access (2023)

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3332243

Artificial intelligence in reproductive medicine

Renjie Wang, Wei Dong Pan, Lei Jin, Yuehan Li et al. • Reproduction (2019)

Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availabilit...

OPENALEX cc-by DOI: https://doi.org/10.1530/rep-18-0523 PMC: 6733338

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Korawege N. C. Jayasena, Battur Batkhishig, Babak Nahid-Mobarakeh, Ali Emadi • IEEE Access (2025)

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predict...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589750

A review of optimization strategies for deep and machine learning in diabetic macular edema

A. M. Mutawa, Khalid Sabti, Bibin Shalini Sundaram Thankaleela, Seemant Raizada • Frontiers in Artificial Intelligence (2026)

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1684752

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

Christoph Balada, Max Bondorf, Sheraz Ahmed, Markus Zdrallek et al. • IEEE Access (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3560811

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry

Philipp Fuchs, Ursula Schmidt-Erfurth, Leonard M. Coulibaly, Hrvoje Bogunovic et al. • Scientific Reports (2025)

Abstract To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monito...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-17417-z

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

Shazia Fathima J.H, Mohammed Sibgatullah, Mohmed Isaqali Karobari • International Journal of Qualitative Methods (2026)

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 ...

DOAJ Open Access (DOAJ) DOI: 10.1177/16094069261504893