The reliability of decision-making algorithms within soft set theory is fundamentally constrained by their underlying membership functions. Traditional binary approaches overlook the implicit connections between the attributes a candidate possesses a...
The desire to improve the safety of navigation, especially in restricted and very busy areas like the straits, leads researchers to evaluate possible uses of Artificial Intelligence as an alternative to the traditional probabilistic methods. This is...
The increasing complexity in hospital waste management requires innovative solutions that integrate sustainability and regulatory compliance. This study proposes an AI-based decision tool to support the circular management of healthcare waste. The ap...
Sustainability targets for livestock require decision support that is both scientifically credible and operationally usable on farms. This integrative narrative review synthesizes the broader peer-reviewed literature on digital farming, artificial in...
Background/Objectives: The use of artificial intelligence (AI) in imaging departments is increasing in Europe. This study assesses the clinical value of an AI fracture algorithm by assessing ease of use, clinicians’ trust, and perceived barrier...
22 August 2020
Artificial intelligence (AI) has made great contributions to the healthcare industry. However, its effect on medical diagnosis has not been well explored. Here, we examined a trial comparing the thinking process between a computer and a master in dia...
Background: Rule-based multi-agent system (MAS) architectures for healthcare coordination rely on hardcoded decision trees that cannot generalise to novel clinical scenarios or self-correct reasoning errors. These limitations are acute in surgical co...
The complexity and magnitude of airspace operations are ever increasing, which creates new challenges for air traffic controllers. With the increase in the volume of operations, the size of available data is also increasing. Data-driven AI solutions...
Accreditation and quality assurance in technical and vocational education and training (TVET) remain largely dependent on manual review and expert judgment. This study presents AccreditNet, an explainable tabular AI model embedded in a broader accred...
Background and Objectives: Integrating large language models (LLMs) such as GPT-4 Turbo into diagnostic imaging faces a significant challenge, with current misdiagnosis rates ranging from 30–50%. This study evaluates how prompt engineering and...
Background/Objectives: Artificial intelligence (AI) tools for fracture detection in radiographs are increasingly approved for clinical use but remain underutilized. Understanding physician attitudes before implementation is essential for successful i...
Background: Subclinical atrial fibrillation (SCAF), a key risk factor for cryptogenic stroke, is difficult to predict with current tools. This study aimed to develop a novel deep learning framework, ResKAN-Attention, using only routine clinical data...
This study proposes a conceptual framework for applying artificial intelligence (AI) to sustainable development projects, emphasizing its role in mitigating risks, enhancing flexibility, and fostering resilience. A case study analysis demonstrates th...
Intensive care medicine represents one of the most challenging setting in modern healthcare, where specific mechanisms intertwine and form a dynamic biological model, where organ dysfunction can easily evolve to multi-organ dysfunction, continuously...
Weather forecasts are crucial in agricultural decision-making. The first objective was to assess the performance of eight weather forecast models for predicting five key meteorological variables in agriculture: air temperature, humidity, wind speed,...
This paper presents the AiD-EM Ontology, which provides a semantic representation of the concepts required to enable the interoperability between multi-agent-based decision support systems, namely AiD-EM, and the market agents that participate in ele...
Artificial Intelligence (AI) is reshaping pharmacy practice by enhancing decision-making, personalizing therapy, and improving medication safety. AI applications now span drug discovery, clinical decision support, and adherence monitoring. This narra...
Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artifi...
Artificial intelligence (AI) is increasingly discussed as a tool for supporting sustainable development in Africa, particularly in healthcare, agriculture, education, and environmental management. However, the feasibility of AI deployment in low-reso...
Background: Artificial intelligence (AI) and large language models (LLMs) may make surgical information easier to access and understand. However, these tools cannot replace the clinician’s role in shared decision-making or the requirements for...
In recent years, Latin America has experienced a growing incorporation of Artificial Intelligence (AI) into business and organizational environments, driven by digital transformation, data availability, and competitive pressures. Across multiple sect...
From a medico-legal perspective, AI functions as a clinical decision support tool without legal autonomy. Responsibility for AI-assisted clinical decisions remains subject to the applicable legal and regulatory framework and depends on the degree of...
Background: The integration of artificial intelligence (AI) in medicine has progressed from rule-based systems to advanced models and is showing potential in clinical decision-making. In this study, the psychological impact of AI collaboration in cli...
As artificial intelligence (AI) is increasingly used in classrooms, tutoring systems, and learning platforms, it is essential that these tools are not only powerful, but also easy to understand, fair, and supportive of real learning. Many current AI...
The rapid integration of Generative Artificial Intelligence (GenAI) technologies into educational environments has generated new opportunities for developing intelligent systems capable of monitoring learner interactions, modeling learning behaviors,...
Artificial intelligence (AI) is rapidly reshaping thoracic surgery, advancing from decision support to the threshold of autonomous intervention. AI-driven technologies—including machine learning (ML), deep learning (DL), and computer vision&mda...
The rapid proliferation of generative artificial intelligence (GenAI) tools has created an urgent need for instruments to evaluate their educational value as teachers, faculty, administrators, and instructional designers consider adopting them. While...
Point-of-care ultrasound (POCUS) is an essential component of emergency medicine, enabling rapid bedside assessment across a wide spectrum of acute conditions. Its effectiveness, however, remains constrained by operator dependency, variable image qua...
Artificial intelligence (AI) is widely expected to transform healthcare, yet its adoption in clinical practice remains limited. This paper examines the perspectives of Italian clinicians and medical physicists on the drivers of and barriers to AI use...
This article reflects on explainability in the context of medical artificial intelligence (AI) applications, focusing on AI-based clinical decision support systems (CDSS). After introducing the concept of explainability in AI and providing a short ov...
This systematic literature review examines how artificial intelligence (AI)-integrated tools are being used to scaffold writing instruction for K-12 English as a Foreign Language (EFL) students, with a particular focus on preserving student agency an...
Recent advances in artificial intelligence (AI) have created opportunities to enhance medical decision-making for patients with discordant chronic conditions (DCCs), where a patient has multiple, often unrelated, chronic conditions with conflicting t...
Artificial intelligence (AI) is increasingly being integrated into medical practice, offering promising tools to improve diagnostic accuracy and clinical efficiency. In the field of breast pathology, AI applications, particularly those based on deep...
Objectives: The increasing incidence of unruptured intracranial aneurysms (UIAs) has led to significant demands on neurovascular boards. Large language models (LLMs), such as ChatGPT-4, ChatGPT-3.5, Claude, and Atlas GPT, have emerged as tools to sup...
Screening for retinal disease is increasingly performed by general practitioners and other non-ophthalmologist clinicians in primary care, especially where access to ophthalmology is limited and diagnostic accuracy may be suboptimal. To investigate t...
Military decision-making is inherently complex and highly critical, requiring commanders to assess multiple variables in real-time, anticipate second-order effects, and adapt strategies based on continuously evolving battlefield conditions. Tradition...
Artificial intelligence (AI) is now a fundamental tool in the development of engineering solutions for prediction, diagnosis, optimization, monitoring, control, and decision support [...]
Forest fire prevention increasingly depends on translating ecological monitoring into earlier, more reliable decisions about ignition risk, fuel condition, spread potential, and management intervention. This critical review evaluates artificial intel...
31 December 2025
This study aimed to examine the role of ChatGPT in supporting travel decision-making by investigating its direct influence and the mediating effects of trust in AI-generated content, perceived usefulness, and perceived ease of use. Data were collecte...
The integration of new technologies in professional contexts has emerged as a critical determinant of organizational efficiency and competitiveness. In this regard, the application of Artificial Intelligence (AI) in recruitment processes facilitates...
GeoAI has advanced the analysis and prediction of urban systems by integrating GIS with artificial intelligence, yet its contribution to urban planning and governance remains limited. Many applications function as black-box predictive tools, making r...
Background: In recent years, Artificial Intelligence (AI) has shown transformative potential in advancing breast cancer care globally. This scoping review seeks to provide a comprehensive overview of AI applications in breast cancer care, examining h...
Efficient water management is increasingly critical in vineyard operations, particularly in the context of climate change and the rising demand for sustainable agricultural practices. Regulated deficit irrigation has emerged as a promising technique...
Artificial intelligence (AI) has generated considerable excitement in radiology, with claims of transformative improvements in diagnostic accuracy, workflow efficiency, and clinical decision support. However, a critical gap persists between AI’...
AI-based decision support is moving into fire practice and governance, where it is used to prioritise inspections, analyse building and community risk, examine station coverage, support evacuation planning, interpret warnings, and explore fire scenar...
Sustainability literacy is increasingly invoked in construction and planning research, yet it is most often framed as an educational construct concerned with awareness, knowledge, and attitudes. This framing provides limited explanatory power for und...
Background/Objectives: Maxillofacial trauma poses significant challenges in emergency medicine, requiring rapid interventions to minimize morbidity and mortality. Traditional segmentation methods are time-consuming and error-prone, particularly in hi...
This research article investigates the synergies between artificial intelligence (AI), digital transformation (DT), and financial reporting systems within the business context. The central theme explores how organizations enhance their decision-makin...
Background: As Artificial Intelligence (AI) proliferates in society, community pharmacists must make decisions as to how to responsibly adopt this technology in their practice. Currently, there are few regulatory requirements or tools to support phar...
This study examines the use of artificial intelligence (AI) in organizational decision-making processes (DMPs) related to investments in renewable energy sources (RESs). The research addresses the gap between AI’s technological capabilities and...
of 20