Search Results (226)

Background: Brain health is a growing public health priority due to the high global burden of neurological and mental disorders. Promoting brain health across the lifespan supports individual and societal well-being, creativity, and productivity. Objective: To address the need for specialized education in this field, the University of Bern developed a Certificate of Advanced Studies (CAS) in Brain Health. This article outlines the program’s rationale, structure, and goals. Program Description: The one-year, 15 ECTS-credit program is primarily online and consists of four modules: (1) Introduction to Brain Health, (2) Brain Disorders, (3) Risk Factors, Protective Factors and Interventions, and (4) Brain Health Implementation. It offers a multidisciplinary, interprofessional, life-course approach, integrating theory with practice through case studies and interactive sessions. Designed for healthcare and allied professionals, the CAS equips participants with skills to promote brain health in clinical, research, and public health contexts. Given the shortage of trained professionals in Europe and globally, the program seeks to build a new generation of brain health advocates. It aims to inspire action and initiatives that support the prevention, early detection, and management of brain disorders. Conclusions: The CAS in Brain Health is an innovative educational response to a pressing global need. By fostering interdisciplinary expertise and practical skills, it enhances professional development and supports improved brain health outcomes at individual and population levels. Full article

Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining underexplored areas and recommending research directions for near-field AR interaction design. Full article

Educational buildings, including schools, nurseries and universities, face stricter regulation and design control on indoor air quality (IAQ) and thermal conditions than other built environments, as these may affect children’s health and wellbeing. In this scoping review, wide-ranging health, performance, and absenteeism consequences of poor—and benefits of good—IAQ and thermal conditions are evaluated, focusing on source control, ventilation and air purification interventions. Economic impacts of interventions in educational buildings have been evaluated to enable the assessment of tangible building-related costs and savings, alongside less easily quantifiable improvements in educational attainment and reduced healthcare. Key recommendations are provided to assist decision makers in pathways to provide clean air, at an optimal temperature for students’ learning and health outcomes. Although the role of educational buildings can be challenging to isolate from other socio-economic confounders, secondary short- and long-term impacts on attainment and absenteeism have been demonstrated from the health effects associated with various pollutants. Sometimes overlooked, source control and repairing existing damage can be important cost-effective methods in minimising generation and preventing ingress of pollutants. Existing ventilation standards are often not met, even when mechanical and hybrid ventilation systems are already in place, but can often be achieved with a fraction of a typical school budget through operational and maintenance improvements, and small-scale air-cleaning and ventilation technologies, where necessary. Full article

Robotic search of people in human-centered environments, including healthcare settings, is challenging, as autonomous robots need to locate people without complete or any prior knowledge of their schedules, plans, or locations. Furthermore, robots need to be able to adapt to real-time events that can influence a person’s plan in an environment. In this paper, we present MLLM-Search, a novel zero-shot person search architecture that leverages multimodal large language models (MLLM) to address the mobile robot problem of searching for a person under event-driven scenarios with varying user schedules. Our approach introduces a novel visual prompting method to provide robots with spatial understanding of the environment by generating a spatially grounded waypoint map, representing navigable waypoints using a topological graph and regions by semantic labels. This is incorporated into an MLLM with a region planner that selects the next search region based on the semantic relevance to the search scenario and a waypoint planner that generates a search path by considering the semantically relevant objects and the local spatial context through our unique spatial chain-of-thought prompting approach. Extensive 3D photorealistic experiments were conducted to validate the performance of MLLM-Search in searching for a person with a changing schedule in different environments. An ablation study was also conducted to validate the main design choices of MLLM-Search. Furthermore, a comparison study with state-of-the-art search methods demonstrated that MLLM-Search outperforms existing methods with respect to search efficiency. Real-world experiments with a mobile robot in a multi-room floor of a building showed that MLLM-Search was able to generalize to new and unseen environments. Full article

Biophilic design has emerged as a multidimensional response to growing concerns about health, well-being, and ecological balance in the built environment. Despite its rising prominence, research on the topic remains fragmented across building typologies, user groups, and geographic contexts. This study presents a comprehensive review of the biophilic design literature, employing a hybrid methodology combining structured content analysis and bibliometric mapping. All peer-reviewed studies indexed in the Web of Science and Scopus were manually screened for architectural relevance and systematically coded. A total of 435 studies were analysed to identify key trends, thematic patterns, and research gaps in the biophilic design discipline. This review categorises the literature by methodological strategies, building typologies, spatial scales, population groups, and specific biophilic design parameters. It also examines geographic and cultural dimensions, including climate responsiveness, heritage buildings, policy frameworks, theory development, pedagogy, and COVID-19-related research. The findings show a strong emphasis on institutional contexts, particularly workplaces, schools, and healthcare, and a reliance on perception-based methods such as surveys and experiments. In contrast, advanced tools like artificial intelligence, simulation, and VR are notably underused. Few studies engage with neuroarchitecture or neuroscience-informed approaches, despite growing recognition of how spatial design can influence cognitive and emotional responses. Experimental and biometric methods remain scarce among the few relevant contributions, revealing a missed opportunity to connect biophilic strategies with empirical evidence. Regarding biophilic parameters, greenery, daylight, and sensory experience are the most studied parameters, while psychological parameters remain underexplored. Cultural and climate-specific considerations appear in relatively few studies, and many fail to define a user group or building typology. This review highlights the need for more inclusive, context-responsive, and methodologically diverse research. By bridging macro-scale bibliometric patterns with fine-grained thematic insights, this study provides a replicable review model and valuable reference for advancing biophilic design as an evidence-based, adaptable, and human-centred approach to sustainable architecture. Full article

Interpreting complex clinical time series is vital for patient safety and care, as it is both essential for supporting accurate clinical assessment and fundamental to building clinician trust and promoting effective clinical action. In complex time series analysis, decomposing a signal into meaningful underlying components is often a crucial means for achieving interpretability. This process is known as time series disentanglement. While deep learning models excel in predictive performance in this domain, their inherent complexity poses a major challenge to interpretability. Furthermore, existing time series disentanglement methods, including traditional trend or seasonality decomposition techniques, struggle to adequately separate clinically crucial specific components: static patient characteristics, condition trend, and acute events. Thus, a key technical challenge remains: developing an interpretable method capable of effectively disentangling these specific components in complex clinical time series. To address this challenge, we propose CoTD-VAE, a novel variational autoencoder framework for interpretable component disentanglement. CoTD-VAE incorporates temporal constraints tailored to the properties of static, trend, and event components, such as leveraging a Trend Smoothness Loss to capture gradual changes and an Event Sparsity Loss to identify potential acute events. These designs help the model effectively decompose time series into dedicated latent representations. We evaluate CoTD-VAE on critical care (MIMIC-IV) and human activity recognition (UCI HAR) datasets. Results demonstrate successful component disentanglement and promising performance enhancement in downstream tasks. Ablation studies further confirm the crucial role of our proposed temporal constraints. CoTD-VAE offers a promising interpretable framework for analyzing complex time series in critical applications like healthcare. Full article

The integration of artificial intelligence into healthcare has advanced rapidly in recent years, with multimodal approaches emerging as promising tools for improving diagnostic accuracy and clinical decision making. These approaches combine heterogeneous data sources such as medical images, electronic health records, physiological signals, and clinical notes to better capture the complexity of disease processes. Despite this progress, only a limited number of studies offer a unified view of multimodal AI applications in medicine. In this review, we provide a comprehensive and up-to-date analysis of machine learning and deep learning-based multimodal architectures, fusion strategies, and their performance across a range of diagnostic tasks. We begin by summarizing publicly available datasets and examining the preprocessing pipelines required for harmonizing heterogeneous medical data. We then categorize key fusion strategies used to integrate information from multiple modalities and overview representative model architectures, from hybrid designs and transformer-based vision-language models to optimization-driven and EHR-centric frameworks. Finally, we highlight the challenges present in existing works. Our analysis shows that multimodal approaches tend to outperform unimodal systems in diagnostic performance, robustness, and generalization. This review provides a unified view of the field and opens up future research directions aimed at building clinically usable, interpretable, and scalable multimodal diagnostic systems. Full article

The rapid growth of the global population and associated increases in resource consumption have accelerated environmental degradation, making sustainable design and construction processes increasingly essential. The construction sector holds significant potential for reducing environmental impacts, especially through sustainability-focused certification systems such as LEED. This study evaluates the projected energy efficiency and sustainability performance of the Surgical Sciences Building at Istanbul University’s Çapa Campus, which was designed with the goal of achieving LEED Gold certification. The assessment is based on design-phase data and conducted prior to construction. Energy performance analyses were carried out using DesignBuilder software, supported by the LEED Assessment Report and Energy Audit Report. According to simulation results, approximately 30% savings in energy consumption and water usage are expected. In addition, the process-oriented LEED approach is expected to result in a total CO₂ emission savings of approximately 570 tonnes, while renewable energy systems are expected to meet approximately 13% of the building’s primary energy demand and reduce CO₂ emissions by approximately 151 tonnes per year. Waste management strategies developed for both the construction and operational phases are aligned with LEED criteria and aim to achieve up to 80% recycling rates. The findings demonstrate that LEED certification, when employed as a process-oriented design and decision-making tool rather than a result-oriented label, can enable sustainable strategies to be integrated from the earliest stages of project development. Particularly for complex healthcare buildings, embedding LEED principles into the design process has strong potential to enhance environmental performance. Although based on a single case study, this research provides valuable insight into the broader applicability of LEED in diverse building types and geographic contexts. Full article

Radiotherapy, a critical component of cancer treatment, faces significant challenges in Gauteng, South Africa. These disparities hinder the achievement of Sustainable Development Goal 3, primarily due to systemic issues, socioeconomic barriers, and limitations within the health system. This article presents the House framework, designed to enhance access to radiotherapy services by integrating the WHO Health Systems framework with the dimensions of access proposed by Penchansky and Thomas. The framework is visually represented as a house, with Policy & Governance as the foundation, WHO building blocks as pillars, and Equitable Cancer Care and Improved Outcomes as the roof. A mixed-methods approach was utilized, combining quantitative data from radiotherapy facilities and qualitative insights from healthcare professionals to identify barriers and potential solutions. Findings indicate significant disparities in resource distribution and accessibility between public and private institutions, compounded by socioeconomic factors like transport costs and lack of awareness. The article discusses innovative proposed framework using the 5As of access as potential solutions. The House framework serves as a valuable tool for policymakers and healthcare providers aiming to improve radiotherapy access and promote equitable cancer care in Gauteng, ultimately working towards reducing disparities in cancer outcomes. Full article

Background: Antimicrobial resistance (AMR) poses a critical global health challenge, particularly in resource-limited settings. A hub-and-spoke model, decentralising expertise and distributing resources to peripheral facilities, has been proposed as a strategy to enhance the antimicrobial stewardship (AMS) capacity in low- and middle-income countries. Aim: This study sought to understand healthcare professionals’ experiences of a hub-and-spoke AMS model in the Volta Region of Ghana and its influence on clinical practice, leadership, and collaborative endeavours to address AMR. Methods: A qualitative descriptive design was adopted. In-depth interviews were conducted with 11 healthcare professionals who participated in the AMS program. Thematic analysis was used to identify key themes related to the knowledge and skills that were gained, clinical and leadership practice changes, capacity building, and challenges. Results: Participants reported an increased awareness of AMR, particularly regarding the scale and clinical implications of antimicrobial misuse. The clinical practice improvements included more judicious prescribing and enhanced adherence to infection prevention and control measures. Many respondents highlighted stronger leadership skills and a commitment to capacity building through AMS committees, multidisciplinary collaboration, and cross-organisational knowledge exchange. Despite resource constraints and logistical hurdles, participants expressed optimism, citing data-driven approaches such as point prevalence surveys to track progress and inform policy. Engagement with hospital management and public outreach were viewed as essential to sustaining AMS efforts and curbing over-the-counter antibiotic misuse. Conclusions: The hub-and-spoke model caused observable improvements in AMS knowledge, clinical practice, and leadership capacity among healthcare professionals in Ghana. While challenges remain, particularly in securing sustainable resources and shifting community behaviours, these findings underscore the potential of network-based programs to catalyse systemic changes in tackling AMR. Future research should explore long-term outcomes and strategies for embedding AMS practices more deeply within healthcare systems and communities. Full article

An increasing number of scholars are raising concerns about the sustainability of digital health, calling for action to prevent its harmful effects on the environment. At this point, however, the comprehensive appraisal of emerging technology in the health sector remains theoretically challenging, and highly difficult to implement in practice and in ecological design. Indeed, background factors such as the rapid evolution of technology or effectiveness–efficiency tradeoffs complicate the task of distinguishing the benefits of digital health from its drawbacks, rendering early Health Technology Sustainability Assessment (HTSA) extremely complex. Within this context, the aim of this article is to draw attention to the pragmatism that should be adopted when anticipating the sustainability of technological innovation in the medical field, while simultaneously proposing an assessment framework grounded in a structural and conceptual dissection of the fundamental purpose of smart technologies and the Internet of Medical Things (IoMT). Building on this, we demonstrate how our framework can be strategically applied through a rapid back-of-the-envelope assessment of the economic and ecological balance when introducing IoMT prototypes for treating a specific condition, based on a preliminary simulation of a defined clinical outcome. In this manner, the article presents evidence that challenges two primary hypotheses, and also encourages reflection on the central role of information and its interpretation when addressing key barriers in the HTSA of digital health. Thereby, it contributes to advancing cost–benefit and cost-effectiveness evaluation tools that support eco design strategies and guide informed decision-making regarding the integration of sustainable IoMT systems into healthcare. Full article

This qualitative study explored the development of an innovative simulation training program designed to bolster the preparedness and resilience of healthcare teams during the unprecedented challenges of the COVID-19 pandemic. Focus groups with interprofessional clinicians illuminated key educational priorities, revealing a need for enhanced safety protocols, clear in communication, and targeted training to address knowledge gaps specific to the novel coronavirus. Recognizing the profound emotional toll of the pandemic, the program also emphasized cultivating compassion and fostering emotional resilience alongside the essential clinical skills. By immersing participants in realistic, evolving scenarios that were reflective of the dynamic COVID-19 landscape, the simulations offered a safe space to rehearse critical skills, practice crisis resource management, and build confidence in navigating the complexities of pandemic care. This tailored approach aimed to empower healthcare teams not only with enhanced knowledge and expertise but also with the emotional fortitude and resilience necessary to provide optimal patient care while safeguarding their own well-being throughout the ongoing COVID-19 pandemic. The findings highlight the profound potential of simulation-based training to strengthen both individual and systemic resilience within healthcare systems facing the enduring strain of this global health crisis. Full article

Objectives: Online healthcare offers an effective solution to reduce regional disparities in medical access. However, building patient trust in a virtual environment, particularly amid digital divide challenges, remains critical for the sustainable development of healthcare platforms. This study investigates how doctors’ professional experience, communicated through online biographies, influences patient consultation decisions, aiming to uncover strategies that enhance trust and facilitate efficient doctor–patient matching. Methods: Drawing on trust theory and social distance theory, we develop an empirical model incorporating professional signals, follower community engagement, and sentiment intensity. Using text data and topic modeling from a leading online health platform, we analyze the impact of these factors on patient consultation behavior. Results: The findings demonstrate that professional experience significantly increases consultation purchases, partially mediated by active follower communities. Additionally, positive emotional expressions in biographies reduce perceived social distance, thereby strengthening trust and willingness to consult. These results highlight the combined effectiveness of professional signals and emotional cues in fostering patient trust. Conclusions: Strategically designed doctor profiles, integrating professional and emotional elements, can bridge the digital divide in online healthcare by enhancing trust and improving doctor-patient matching. This study advances the understanding of how online biographical narratives shape trust and decision-making, offering novel insights into the interplay of doctor-generated content, trust, and social distance. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly integrated into everyday life, including the complex and highly regulated healthcare sector. Given healthcare’s essential role in safeguarding human life and well-being, AI deployment requires careful oversight to ensure safety, effectiveness, and ethical compliance. This paper aims to examine the current regulatory landscapes governing AI in healthcare, particularly in the European Union (EU) and the United States (USA), and to propose practical tools to support the responsible development and implementation of AI systems. Methods: The study reviews key regulatory frameworks, ethical guidelines, and expert recommendations from international bodies, professional associations, and governmental institutions in the EU and USA. Based on this analysis, the paper develops structured questionnaires tailored for AI developers and implementers to help operationalize regulatory and ethical expectations. Results: The proposed questionnaires address critical gaps in existing frameworks by providing actionable, lifecycle-oriented tools that span AI development, deployment, and clinical use. These instruments support compliance and ethical integrity while promoting transparency and accountability. Conclusions: The structured questionnaires can serve as practical tools for health technology assessments, public procurement, accreditation processes, and training initiatives. By aligning AI system design with regulatory and ethical standards, they contribute to building trustworthy, safe, and innovative AI applications in healthcare. Full article

Data integration (DI) and semantic interoperability (SI) are critical in healthcare, enabling seamless, patient-centric data sharing across systems to meet the demand for instant, unambiguous access to health information. Federated information systems (FIS) highlight auspicious issues for seamless DI and SI stemming from diverse data sources or models. We present a hybrid ontology-based design science research engineering (ODSRE) methodology that combines design science activities with ontology engineering principles to address the above-mentioned issues. The ODSRE constructs a systematic mechanism leveraging the Ontop virtual paradigm to establish a state-of-the-art federated virtual knowledge graph framework (FVKG) embedded virtualized knowledge graph approach to mitigate the aforementioned challenges effectively. The proposed FVKG helps construct a virtualized data federation leveraging the Ontop semantic query engine that effectively resolves data bottlenecks. Using a virtualized technique, the FVKG helps to reduce data migration, ensures low latency and dynamic freshness, and facilitates real-time access while upholding integrity and coherence throughout the federation system. As a result, we suggest a customized framework for constructing ontological monolithic semantic artifacts, especially in FIS. The proposed FVKG incorporates ontology-based data access (OBDA) to build a monolithic virtualized repository that integrates various ontological-driven artifacts and ensures semantic alignments using schema mapping techniques. Full article