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Background: Conventional HIV testing approaches continue to fall short of overcoming barriers to HIV testing, especially among key and priority populations at higher risk of acquiring and transmitting HIV. Artificial in...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

This book is a material aimed at training new graduates and updating practising professionals within the framework of early childhood care (0-6 years). It also opens up training to new professions such as health engineer...

In the recent years, a dramatic boost of the research is observed at the junction of photonics, machine learning and artificial intelligence. A new methodology can be applied to the description of a variety of photonic s...

One current research goal of Artificial Intelligence and Machine Learning is to improve the problem-solving performance of systems with their own experience or from external teaching. The work presented in this paper co...

BackgroundArtificial intelligence (AI) has substantial potential to advance periodontal and peri- implant care through novel diagnostic, prognostic, and therapeutic opportunities. Nevertheless, the evidence is scattered ...

Background: Climate change increasingly shapes development outcomes, necessitating its integration into evaluation processes. In Africa, recurrent droughts, floods and temperature extremes disrupt progress across sector...

The application of Artificial Intelligence (AI) in project management is transforming decision-making processes, enhancing task execution, and improving risk management. This study aimed to elucidate the challenges raise...

Malignant tumors pose a significant global health challenge. While established screening methods exist, they are largely site-specific, limiting comprehensive prevention. Multi-cancer screening, which detects multiple ca...

Abstract Objective Acute heart failure (AHF) is a common but underrecognized cause of dyspnea. Chest computed tomography (CT) can accurately assess pulmonary congestion, but radiologist reporting capacity may limit clini...

Recent developments in artificial intelligence (AI) have made significant improvements in understanding and enhancing pedestrian safety—a vulnerable road user group that receives less attention than motorized road user...

Abstract Background Tuberculous pericardial effusion (TPE) presents significant diagnostic challenges due to its nonspecific clinical presentation and similarities with other types of pericardial effusion. The available ...

Abstract This model is highly helpful in thermal management and complex energy systems, particularly where precise control over heat and mass transfer is required. Solarized nanofluids can be used to improve heat absorpt...

The sustainable utilization of post-consumer waste glass in concrete has emerged as a promising approach to reduce cement consumption, mitigate landfill disposal, and enhance material performance. However, most previous ...

Artificial intelligence (AI), including machine learning, deep learning, reinforcement learning, and generative AI, has the potential to advance critical care nephrology (CCN) by enhancing prediction accuracy, improving ...

Empowering nanophotonic devices via artificial intelligence (AI) has revolutionized both scientific research methodologies and engineering practices, addressing critical challenges in the design and optimization of compl...

One of the main sectors that makes heavy use of the development of advanced computational methods is the banking sector. The goals of our research are as follows: 1) to compare scientific and regulatory approaches to def...

Abstract Background Effective modeling and parametric studies strengthen analyses of the influence of cotton fiber properties on the yarn properties, which are important for developing a higher-quality product. Machine l...

This study examines the application of artificial intelligence in analyzing and understanding the urban morphology of Zanjan. The primary objective of this research is to propose a machine learning-based framework for th...

Abstract Despite significant progress in the Prognostics and Health Management (PHM) domain using pattern learning systems from data, machine learning (ML) still faces challenges related to limited generalization and wea...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

Abstract Background Understanding how the respiratory microbiota matures with age is key to improving poultry health and pathogen surveillance, yet the ecological processes shaping this transition remain elusive. We aime...

Background: The development of accurate artificial intelligence (AI) models for liver cancer diagnosis using contrast-enhanced computed tomography (CT) is often hindered by patient privacy regulations and considerable da...

Abstract Financial institutions continue to face a significant challenge with money laundering and need intelligent, scalable ways to detect illegal financial activity. This paper introduces a machine learning-driven pla...