Research (15)
A cerebrospinal fluid synaptic protein biomarker for prediction of cognitive resilience versus decline in Alzheimer’s disease
Rates of cognitive decline in Alzheimer’s disease (AD) are extremely heterogeneous. Although biomarkers for amyloid-beta (Aβ) and tau proteins, the hallmark AD pathologies, have improved pathology-based diagnosis, they explain only 20–40% of the variance in AD-related cognitive impairment (CI). To discover novel biomarkers of CI in AD, we performed cerebrospinal fluid (CSF) proteomics on 3,397 individuals from six major prospective AD case–control cohorts. Synapse proteins emerged as the stronge
The impact of generative <scp>AI</scp> on academic integrity of authentic assessments within a higher education context
Generative AI (hereinafter GenAI) technology, such as ChatGPT, is already influencing the higher education sector. In this work, we focused on the impact of GenAI on the academic integrity of assessments within higher education institutions, as GenAI can be used to circumvent assessment approaches within the sector, compromising their quality. The purpose of our research was threefold: first, to determine the extent to which the use of GenAI can be detected via the marking and moderation process
Purposeful sampling and saturation in qualitative research methodologies: recommendations and review
Abstract Qualitative research has been flourishing in business and management research over the past decades. The insights gathered from rich qualitative data fundamentally depend on the analyzed subjects and case(s). Hence, highly substantial to qualitative research is how to achieve purposeful case selection and saturation of cases and informants. Our study reviews previous research on purposeful case selection and saturation. We specify that considering the level of analysis is particularly c
A Review of the Industry 4.0 to 5.0 Transition: Exploring the Intersection, Challenges, and Opportunities of Technology and Human–Machine Collaboration
The Industrial Revolution (IR) involves a centuries-long process of economic and societal transformation driven by industrial and technological innovation. From agrarian, craft-based societies to modern systems powered by Artificial Intelligence (AI), each IR has brought significant societal advancements yet raised concerns about future implications. As we transition from the Fourth Industrial Revolution (IR4.0) to the emergent Fifth Industrial Revolution (IR5.0), similar questions arise regardi
Disclosing artificial intelligence use in scientific research and publication: When should disclosure be mandatory, optional, or unnecessary?
Currently there is a broad consensus among scholars that artificial intelligence (AI) tools can be used in research and publication, and that their use should be disclosed. Publishers and influential organizations, like the International Committee of Medical Journal Editors, have developed different and sometimes contradictory disclosure policies. We review some of these policies, examine the ethical reasons for disclosing AI use in research, and develop a framework for disclosure. We distinguis
Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis
Artificial intelligence (AI) has quickly emerged as a top technological priority for companies in various sectors, radically altering business operations. However, the existing literature reveals a fragmented and inconsistent understanding of AI adoption dynamics between small and medium enterprises (SMEs) and larger, well-established firms. This dichotomy of the existing research raises important questions about whether the AI tools and application modalities used by these companies are inheren
Machine Learning and Artificial Intelligence in the Multi-Omics Approach to Gut Microbiota
The gut microbiome is involved in human health and disease, and its comprehensive understanding is necessary to exploit it as a diagnostic or therapeutic tool. Multi-omics approaches, including metagenomics, metatranscriptomics, metabolomics, and metaproteomics, enable depiction of the gut microbial ecosystem's complexity. However, these tools generate a large data stream in which integration is needed to produce clinically useful readouts, but, in turn, might be difficult to carry out with conv
From virtual to reality: innovative practices of digital twins in tumor therapy
BACKGROUND: As global cancer incidence and mortality rise, digital twin technology in precision medicine offers new opportunities for cancer treatment. OBJECTIVE: This study aims to systematically analyze the current applications, research trends, and challenges of digital twin technology in tumor therapy, while exploring future directions. METHODS: Relevant literature up to 2024 was retrieved from PubMed, Web of Science, and other databases. Data visualization was performed using R and VOSviewe
Early warning of complex climate risk with integrated artificial intelligence
As climate change accelerates, human societies face growing exposure to disasters and stress, highlighting the urgent need for effective early warning systems (EWS). These systems monitor, assess, and communicate risks to support resilience and sustainable development, but challenges remain in hazard forecasting, risk communication, and decision-making. This perspective explores the transformative potential of integrated Artificial Intelligence (AI) modeling. We highlight the role of AI in devel
Understanding Customer Responses to AI-Driven Personalized Journeys: Impacts on the Customer Experience
Within advertising, the customer journey concept helps explain how customer perceptions and behaviors evolve through seller–customer interactions. The concept has developed to reflect omni-channel marketing but neglects the emergence of algorithmically personalized advertisements. This study therefore explores impacts upon customer experiences of artificial intelligence (AI)-driven recommendations and personalized advertisements by analyzing customer perceptions of tensions between the personali
The Role of AI in Nursing Education and Practice: Umbrella Review
BACKGROUND: Artificial intelligence (AI) is rapidly transforming health care, offering substantial advancements in patient care, clinical workflows, and nursing education. OBJECTIVE: This umbrella review aims to evaluate the integration of AI into nursing practice and education, with a focus on ethical and social implications, and to propose evidence-based recommendations to support the responsible and effective adoption of AI technologies in nursing. METHODS: We included systematic reviews, sco
Towards an AI-Literate Future: A Systematic Literature Review Exploring Education, Ethics, and Applications
Abstract This study investigates the evolving landscape of Artificial Intelligence (AI) literacy, acknowledging AI's transformative impact across various sectors in the twenty-first century. Starting from AI's inception to its current pervasive role in education, everyday life, and beyond, this paper explores the relevance and complexity of AI literacy in the modern world. To evaluate the current state of the literature on AI literacy, a systematic literature review was conducted with the object
The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview. Part 1: Fundamentals of AI, and its Contemporary Applications in Dentistry
Artificial intelligence (AI) holds immense promise in revolutionising dentistry, spanning, diagnostics, treatment planning and educational realms. This narrative review, in two parts, explores the fundamentals and the multifaceted potential of AI in dentistry. The current article explores the profound impact of AI in dentistry, encompassing diagnostic tools, treatment planning, and patient care. The Part 2 of the article delves into the potential of AI in patient education, ethics and the FDI co
The role of explainable artificial intelligence in disease prediction: a systematic literature review and future research directions
Explainable Artificial Intelligence (XAI) enhances transparency and interpretability in AI models, which is crucial for trust and accountability in healthcare. A potential application of XAI is disease prediction using various data modalities. This study conducts a Systematic Literature Review (SLR) following the PRISMA protocol, synthesizing findings from 30 selected studies to examine XAI's evolving role in disease prediction. It explores commonly used XAI methods, such as Shapley Additive Exp
Dietary Phytochemicals in Health and Disease: Mechanisms, Clinical Evidence, and Applications—A Comprehensive Review
Phytochemicals are bioactive compounds found in plants that play a key role in promoting health and preventing diseases. Present in fruits, vegetables, grains, and seed oils, these compounds are considered safe for consumption due to the co-evolution and adaptation between mammals and plants. Due to their wide-ranging biological effects, they have attracted considerable research interest. This comprehensive review explores the mechanisms of action, health benefits, and applications of dietary ph