Search Results (73)

Brain metastases (BMs) are the most common intracranial tumors in adults. Their heterogeneity, potential multifocality, and complex biomolecular behavior pose significant diagnostic and therapeutic challenges. Artificial intelligence (AI) has the potential to revolutionize BM diagnosis by facilitating early lesion detection, precise imaging segmentation, and non-invasive molecular characterization. Machine learning (ML) and deep learning (DL) models have shown promising results in differentiating BMs from other intracranial tumors with similar imaging characteristics—such as gliomas and primary central nervous system lymphomas (PCNSLs)—and predicting tumor features (e.g., genetic mutations) that can guide individualized and targeted therapies. Intraoperatively, AI-driven systems can enable optimal tumor resection by integrating functional brain maps into preoperative imaging, thus facilitating the identification and safeguarding of eloquent brain regions through augmented reality (AR)-assisted neuronavigation. Even postoperatively, AI can be instrumental for radiotherapy planning personalization through the optimization of dose distribution, maximizing disease control while minimizing adjacent healthy tissue damage. Applications in systemic chemo- and immunotherapy include predictive insights into treatment responses; AI can analyze genomic and radiomic features to facilitate the selection of the most suitable, patient-specific treatment regimen, especially for those whose disease demonstrates specific genetic profiles such as epidermal growth factor receptor mutations (e.g., EGFR, HER2). Moreover, AI-based prognostic models can significantly ameliorate survival and recurrence risk prediction, further contributing to follow-up strategy personalization. Despite these advancements and the promising landscape, multiple challenges—including data availability and variability, decision-making interpretability, and ethical, legal, and regulatory concerns—limit the broader implementation of AI into the everyday clinical management of BMs. Future endeavors should thus prioritize the development of generalized AI models, the combination of large and diverse datasets, and the integration of clinical and molecular data into imaging, in an effort to maximally enhance the clinical application of AI in BM care and optimize patient outcomes. Full article

Background/Objectives: To avoid becoming mired in prolonged deep dementia, some people seek to hasten death by advance instructions rejecting life-sustaining medical intervention (LSMI) at a point of cognitive decline they define in advance as unacceptable. When the time comes to implement such advance instructions and to allow the person in advanced dementia to die, many clinicians experience moral and ethical qualms. The decision makers face a clash between people’s legally recognized self-determination prerogative to control their post-competence medical fate and the decision makers’ conviction that humane treatment dictates sustaining the well-being, i.e., the physical “best interests,” of the patient who no longer recalls prior instructions grounded in concerns about personal dignity. The authors’ objective here is to provide guidance in resolving this anguishing dilemma confronting medical decision makers. Methods: The authors construct and analyze a case scenario involving a patient in a state of advanced dementia with a clear advance instruction rejecting LSMI at the current point of debilitation, but who is not ostensibly suffering, is experiencing a modicum of life satisfaction, and is making life-affirming utterances. The two lead authors present contrasting views on whether legal and moral factors impel the implementation of the advance directive rejecting treatment or rather dictate life-sustaining medical intervention. Results: At this early stage of jurisprudence involving persons in advanced dementia, there can be no definitive resolution of the difficult legal/moral clash confronting decision makers. Some sources would conclude that persons are legally entitled to define precipitous mental decline and complete dependence on others as intolerably undignified and inconsistent with their self-defined life narrative. Other sources would be guided by humane respect for the contemporary well-being of a non-suffering patient, especially one making life-affirming utterances. Conclusion: Through the lens of this illuminating case and contrasting analyses, readers should better understand how clinicians should weigh advance directives against shifting care preferences subsequently articulated by persons with advanced dementia. Full article

Introduction: The effective and meaningful use of anonymized personal data, including open data, is globally significant across various sectors. Enhancing data utilization aims to generate substantial societal benefits and added value through innovations, products, and services. However, several legal, ethical, and technical challenges currently hinder the development and broader adoption of open data. Furthermore, the availability of technical support tools with high usability is especially desirable to facilitate the anonymization process effectively. Methods: As part of the EAsyAnon research project, preliminary insights were gathered through a scoping review that identified factors promoting or impeding the anonymization and use of personal data. Based on these findings, a structured interview guide was developed. Following a pretest, 19 interviews were conducted with diverse stakeholders from healthcare institutions, research organizations, public authorities, and private companies. The collected data were analyzed using Kuckartz’s structural content analysis methodology, supported by qualitative analysis software. Results: The content analysis yielded five overarching categories and 21 subcategories. These encompassed stakeholder experiences related to anonymization and open data processes, the various types and formats of personal data, identified barriers and enabling factors, support services, and the ethical and legal considerations associated with anonymization. Discussion: The findings highlight significant uncertainty among stakeholders regarding the anonymization of personal data. Although the importance and potential applications of open data for innovation and continuous improvement are widely acknowledged and supported, numerous challenges persist at both the macro and micro levels. The results emphasize a clear need for targeted support measures to address these challenges effectively. Full article

The present study addresses the need for valid and reliable tools to assess employability thinking among young people in training. In a labor market increasingly shaped by transversal skill demands, the objective was to construct and validate a scale adapted for secondary and post-secondary non-tertiary students. Grounded in strategic frameworks such as the Europe 2020 Strategy, the European Skills Agenda, and relevant Spanish legislation, an abbreviated version of the Graduate Skills and Attributes Scale (GSAS) was administered to a representative sample of 949 Andalusian students enrolled in compulsory secondary education, baccalaureate, or vocational training. A cross-sectional and exploratory research design was adopted, with all procedures conducted in accordance with ethical and legal standards and approved by the University of Granada’s ethics committee. Exploratory and confirmatory factor analyses were performed, leading to a refined 28-item version of the instrument. Items were grouped into four well-defined factors: ethical self-regulation and achievement orientation, effective communication and collaborative working, proactivity and commitment to learning, and analytical thinking and information handling. The factors demonstrated high internal consistency and structural validity. These findings indicate that the scale is a clear and effective tool for assessing employability-related competencies and may assist in the design of educational interventions aimed at improving students’ professional development. Full article

Background: Solid organ transplantation, which began as an experimental procedure over 100 years ago, has now become a viable therapeutic option for the vast majority of patients with end-stage organ failure. However, a major limiting factor remains the shortage of organs available for transplantation. To expand the donor pool, it is essential to increase awareness of transplantation, including its legal, cultural, and ethical aspects. Every year, numerous organizations, primarily non-governmental, organize hundreds of campaigns promoting transplantation worldwide. The majority of these initiatives are one-time events tied to observances such as World Transplant Day, World Kidney Day, and others. The growing role of social media in spreading information is also becoming a key factor in promoting organ donation and transplantation, as social factors play an important role in expanding the donor pool. Many organizations that support transplantation, along with healthcare providers, widely use platforms like Facebook and other social media to promote and increase organ donation. Objectives: The “Second Life” is a social campaign presentation to raise awarenes about transplantation. Project Description: The campaign has been running continuously for 17 years in Poland, promoting the concepts of organ donation and transplantation in collaboration with high school students. During this time, 950 high schools across the country participated in the project, with approximately 450,000 high school students actively engaging in the campaign. Outcomes: They organized a series of activities to promote organ donation and transplantation within their social circles, distributing nearly 1.5 million declarations of will. Additionally, they helped raise awareness about presumed consent and educated others on the concepts of organ donation and transplantation. Conclusions/Implications: This long-term initiative is crucial for raising awareness, educating the public, and promoting the idea of organ donation. It fosters a more positive attitude toward organ donation and transplantation, ultimately contributing to the expansion of the donor pool and an increase in transplantations in the near future. Full article

Background/Objectives: Competing endogenous RNAs (ceRNA) are molecules that compete for the binding to a microRNA (miR). Usually, there are two ceRNA, one of which is a protein-coding RNA (mRNA), with the other being a long non-coding RNA (lncRNA). The miR role is to inhibit mRNA expression, either promoting its degradation or impairing its translation. The lncRNA can “sponge” the miR, thus impeding its inhibitory action on the mRNA. In their easier configuration, these three molecules constitute a regulatory axis for protein expression. However, each RNA can interact with multiple targets, creating branched and intersected axes that, all together, constitute what is known as a competing endogenous RNA network (ceRNET). Methods: In this systematic review, we collected all available data from PubMed about experimentally verified (by luciferase assay) regulatory axes in endometrial cancer (EC), excluding works not using this test; Results: This search allowed the selection of 172 bibliographic sources, and manually building a series of ceRNETs of variable complexity showed the known axes and the deduced intersections. The main limitation of this search is the highly stringent selection criteria, possibly leading to an underestimation of the complexity of the networks identified. However, this work allows us not only to hypothesize possible gap fillings but also to set the basis to instruct artificial intelligence, using adequate prompts, to expand the EC ceRNET by comparing it with ceRNETs of other cancers. Moreover, these networks can be used to inform and guide research toward specific, though still unidentified, axes in EC, to complete parts of the network that are only partially described, or even to integrate low complexity subnetworks into larger more complex ones. Filling the gaps among the existing EC ceRNET will allow physicians to hypothesize new therapeutic strategies that may either potentiate or substitute existing ones. Conclusions: These ceRNETs allow us to easily visualize long-distance interactions, thus helping to select the best treatment, depending on the molecular profile of each patient, for personalized medicine. This would yield higher efficiency rates and lower toxicity levels, both of which are extremely relevant factors not only for patients’ wellbeing, but also for the legal, regulatory, and ethical aspects of miR-based innovative treatments and personalized medicine as a whole. This systematic review has been registered in PROSPERO (ID: PROSPERO 2025 CRD420251035222). Full article

Introduction: African healthcare professionals face significant mental health challenges; therefore, telemedicine can overcome geographical barriers and improve access to mental healthcare. Objective: The objective of this study was to identify the key factors influencing the adoption of telemedicine as a tool to support healthcare workers’ mental health in an Angolan healthcare network and develop a telemedicine model tailored to this context. Methodology: This mixed-method study collected quantitative data from a questionnaire applied to healthcare workers (n = 275), which were analyzed using descriptive statistics and logistic regressions. Qualitative data were obtained through structured interviews (n = 5) with psychologists and psychiatrists, and analyzed using thematic analysis in MAXQDA (Version 2022, VERBI Software, Germany), to identify recurring patterns and themes. The data were triangulated to ensure the rigor and consistency of the findings. Participation was anonymous and voluntary, and informed consent was obtained from all participants. Results: Previous experiences with mental health consultations, perceptions of teleconsultations, and doctor–patient relationship were significant in influencing telemedicine adoption by workers. The thematic analysis revealed four themes: perception and ease of telemedicine use, intention to use, and the perception of mental health in Angola. The key adoption factors for providers included project feasibility, management support, training, payment policies, and adherence to legal, ethical, and deontological standards. Conclusions: The adoption of telemedicine for occupational mental health requires culturally adapted interventions and compliance with technological and data protection standards. Hospital management must address infrastructure challenges and mental health perceptions, and implement sustainable strategies that promote occupational well-being within the organization. Full article

Background/Objectives: Esophageal cancer (EC) represents a major global contributor to cancer-related mortality. The advent of artificial intelligence (AI), including machine learning, deep learning, and radiomics, holds promise for enhancing treatment decisions and predicting outcomes. The aim of this review is to present an overview of the current landscape and future perspectives of AI in the management of EC. Methods: A literature search was performed on MEDLINE using the following keywords: “Artificial Intelligence”, “Esophageal cancer”, “Barrett’s esophagus”, “Esophageal Adenocarcinoma”, and “Esophageal Squamous cell carcinoma”. All titles and abstracts were screened; the results included 41 studies. Results: Over the past five years, the number of studies focusing on the application of AI to the treatment and prognosis of EC has surged, leveraging increasingly larger datasets with external validation. The simultaneous incorporation in AI models of clinical factors and features from several imaging modalities displays improved predictive performance, which may enhance patient outcomes, based on direct personalized therapeutic options. However, clinicians and researchers must address existing limitations, conduct randomized controlled trials, and consider the ethical and legal aspects that arise to establish AI as a standard decision-support tool. Conclusions: AI applications may result in substantial advances in EC management, heralding a new era. Considering the complexity of EC as a clinical entity, the evolving potential of AI is anticipated to ameliorate patients’ quality of life and survival rates. Full article

Background: The legalization of euthanasia in Belgium in 2002 positioned nurses as possible participants in the euthanasia process. However, ethical and legal dilemmas necessitate clear definitions of their roles and competencies in this context. Given that general practitioners (GPs) are the primary medical professionals performing euthanasia, understanding their perspectives on the roles of nurses is crucial. Aim: This study aims to describe GPs’ perceptions of the roles and competencies of nurses during the euthanasia process. The research question addressed is as follows: “What are GPs’ views on the roles and competencies of nurses in euthanasia?”. Methods: A quantitative cross-sectional survey was conducted among licensed GPs in Flanders, Belgium. Data were collected via an online survey using Qualtrics and analyzed with SPSS Statistics. Ethical approval was obtained from the Medical Ethics Committee of the university. Results: The study included responses from 237 GPs. GPs value the roles and competencies of nurses, recognizing euthanasia as a multidisciplinary process. They acknowledge the critical support nurses provide to patients and their families. GPs assert that the administration of euthanasia medication should remain the exclusive responsibility of the GP. The analysis further indicated that demographic factors did not significantly influence the results. Discussion/Conclusions: GPs in Belgium generally rated the roles and competencies of nurses positively. Enhancing multidisciplinary collaboration, legislating the roles of nurses, and incorporating practical euthanasia training in nursing curricula, e.g., via simulations, are recommended. Full article

Amidst the rapid digital transformation reshaping the legal profession globally, this study examines the interplay between AI tools, social media usage, and lawyer job performance in China. While prior research has extensively explored factors influencing the job performance of lawyers, due to the relatively small number of lawyers in China and the legal and ethical limitations in their use of social media and AI tools, systematic investigations into the roles of AI and social media in this context remain limited. We use an ensemble Bayesian network model to examine causal mechanisms, analyzing 313 questionnaires on their use of AI and social media. This study constructs a robust causal network to analyze the impacts of nine key variables, including excessive social use of social media at work, AI-supported employee training and development, AI-driven workload reduction for employees, and strain, among others. The findings reveal that AI-driven workload reduction, AI-supported leadership, and strain directly influence lawyer job performance. Notably, excessive cognitive use of social media at work (ECU) exerts the most significant impact, while strain and work–technology conflict serve as critical mediators in the relationship between ECU and performance. The ensemble Bayesian network framework not only enhances the methodological rigor of this research but also facilitates a comprehensive understanding of the complex interdependencies among the considered factors. Based on the results, practical recommendations are proposed for the optimization of the job performance of lawyers. This study contributes to the growing body of literature on lawyer job performance through the introduction of an advanced analytical approach, as well as offering actionable insights for law firms and informing legal technology legislation and policy development navigating the digital era. Full article

Background: The ultra-rare nature of melanoma in children, adolescents, and young adults poses significant challenges to the development and implementation of effective prevention and diagnostic strategies. This article delves into the ELSIs surrounding these strategies, placing particular emphasis on the transformative potential of AI-driven tools and applications. Methods: Using an exploratory sequential mixed methods approach, this study integrated a PICO-guided literature review and qualitative insights from two focus groups. The review included 26 peer-reviewed articles published in English from January 2019 to January 2024, addressing ELSIs in melanoma, rare diseases, and AI in dermatology. Focus groups included a March 2024 session in Berlin with 15 stakeholders (patients, caregivers, advocates, healthcare professionals) and a November 2024 online session with 5 interdisciplinary experts. Results: Six key priorities for healthcare policies emerged: addressing cultural factors, such as the glorification of tanned skin; enhancing professional training for accurate diagnosis; balancing the risks of overdiagnosis and underdiagnosis; promoting patient autonomy through transparent communication; reducing inequalities to ensure equitable access to care; and making ethical and legal use of AI in healthcare. Conclusion: These priorities provide a comprehensive framework for advancing the prevention and diagnosis of melanoma in children, adolescents, and young adults, leveraging AI technologies while prioritizing equitable and patient-centered healthcare delivery. Full article

Background: Artificial intelligence (AI) has recently made unprecedented contributions in every walk of life, but it has not been able to work its way into diagnostic medicine and standard clinical practice yet. Although data scientists, researchers, and medical experts have been working in the direction of designing and developing computer aided diagnosis (CAD) tools to serve as assistants to doctors, their large-scale adoption and integration into the healthcare system still seems far-fetched. Diagnostic radiology is no exception. Imagining techniques like magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans have been widely and very effectively employed by radiologists and neurologists for the differential diagnoses of neurological disorders for decades, yet no AI-powered systems to analyze such scans have been incorporated into the standard operating procedures of healthcare systems. Why? It is absolutely understandable that in diagnostic medicine, precious human lives are on the line, and hence there is no room even for the tiniest of mistakes. Nevertheless, with the advent of explainable artificial intelligence (XAI), the old-school black boxes of deep learning (DL) systems have been unraveled. Would XAI be the turning point for medical experts to finally embrace AI in diagnostic radiology? This review is a humble endeavor to find the answers to these questions. Methods: In this review, we present the journey and contributions of AI in developing systems to recognize, preprocess, and analyze brain MRI scans for differential diagnoses of various neurological disorders, with special emphasis on CAD systems embedded with explainability. A comprehensive review of the literature from 2017 to 2024 was conducted using host databases. We also present medical domain experts’ opinions and summarize the challenges up ahead that need to be addressed in order to fully exploit the tremendous potential of XAI in its application to medical diagnostics and serve humanity. Results: Forty-seven studies were summarized and tabulated with information about the XAI technology and datasets employed, along with performance accuracies. The strengths and weaknesses of the studies have also been discussed. In addition, the opinions of seven medical experts from around the world have been presented to guide engineers and data scientists in developing such CAD tools. Conclusions: Current CAD research was observed to be focused on the enhancement of the performance accuracies of the DL regimens, with less attention being paid to the authenticity and usefulness of explanations. A shortage of ground truth data for explainability was also observed. Visual explanation methods were found to dominate; however, they might not be enough, and more thorough and human professor-like explanations would be required to build the trust of healthcare professionals. Special attention to these factors along with the legal, ethical, safety, and security issues can bridge the current gap between XAI and routine clinical practice. Full article

Museum collections serve as valuable repositories of biodiversity, offering a substantial amount of data and specimens for scientific research. This study describes the intrinsic value of the mammal collection at the National Museum of Natural History and Science of the University of Lisbon (Portugal) (MUHNAC), and its nationwide representativeness, with the final aim of revealing its potential to support research and conservation initiatives. The collection includes 6158 specimens, from 131 species, across 10 orders, the great majority collected within Portugal, although a small dataset mostly from other parts of Europe and Africa is also available. The most represented orders are Rodentia, Eulipotyphla, and Carnivora, in contrast to Chiroptera, Cetacea, and Artiodactyla. Approximately 40% of the species within these groups are of conservation concern according to both national and international conventions, with nearly 20% at risk of extinction based on IUCN criteria. Additionally, the representativity of species in MUHNAC reflects the museum’s coverage of species records across the country, with smaller, non-threatened species being more prominently represented and larger, at-risk species being comparatively underrepresented. The influence of conservation, economic, legal, and ethical factors on the species spatial coverage is discussed, providing insights into the variability observed in museum collections. Full article

This paper presents the research findings on Public-Private Partnerships (PPP) brief development in the United Arab Emirates. A questionnaire survey was conducted to assess and rank the relative importance of the Critical Success Factors (CSFs) identified in PPP brief development in the UAE. A quantitative analysis was then conducted on the data gathered from the survey, and the results of the analysis are described. The processes of purifying and computing the measurement instruments are also explored using Cronbach’s alpha to assess the reliability of scale measurements. The statistical analysis focuses on the importance and ranking of the identified thirty-eight (38) CSFs and their Sub-Success Factors (SSFs). The overall assessment of these factors highlights their importance in a brief development process. Accordingly, these factors are grouped into seven categories, and the developed CSF framework is presented. The categories, listed in descending order, are Regulatory and Legal Factors; Finance and Economic Factors; Risk-Related Factors; Public Sector Capacity-Related Factors; Procurement-Related Factors; Stakeholder-Related Factors; and Social, Cultural, and Ethical Factors. The research findings offer a comprehensive framework of CSFs for brief development tailored to the unique PPP environment of the UAE to ensure project success. Full article

Veterinarians face ethical challenges during their careers, but despite evidence of work-related stress and burnout in veterinarians, moral distress has been poorly investigated. Using an online survey, professional experience, moral distress, and burnout were investigated in 704 Italian veterinarians caring for companion animals, farm animals, or both. The reliability of the moral distress questionnaire was optimal, and Factor analysis identified four factors for moral distress: I. Conflict with owner/farmer; II. Relationships with colleagues/superiors; III. Legal context/unsupportive Professional Institutions; IV. Unshared requests for euthanasia. Veterinarians reported rather low levels of moral distress but high levels of work-related stress/anxiety and a decline in empathy over time, mainly toward owners/farmers. More than 50% of veterinarians reported medium/high levels of burnout, and client-related burnout was significantly higher than animal-related burnout. Levels of work-related stress, moral distress, and burnout were higher in women, and experience exerted a protective effect. Moral distress was positively correlated with emotional exhaustion and depersonalization and, to a lesser extent, lower professional fulfillment. The relatively low level of moral distress that emerged in the study needs further investigation, especially considering the high levels of work-related stress and anxiety reported by veterinarians. Women’s greater sensitivity to moral distress and burnout should not be overlooked given the progressive feminization of the veterinary profession worldwide. Full article