Search Results (2,493)

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. This paper presents a systematic review of the scientific literature published between 1 January 2020 and 31 May 2025. The paper is based on the applicability of ML techniques in the field of geriatrics. The study is conducted using the Web of Science database for a detailed discussion. The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. The performance metrics reported in the analyzed papers include the accuracy, sensitivity, F1-score, and Area under the Receiver Operating Characteristic Curve. Nine search categories are investigated through four databases: WOS, PubMed, Scopus, and IEEE. A comparative analysis shows that the field of geriatrics, through an ML approach in the context of elderly nutrition, is insufficiently explored, as evidenced by the 61 articles analyzed from the four databases. The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. The paper highlights the potential of ML models in transforming geriatrics within the context of personalized predictive care and outlines a series of future research directions, recommending the development of standardized databases, the integration of algorithmic explanations, the promotion of interdisciplinary collaborations, and the implementation of ethical norms of artificial intelligence in geriatric medical practice. Full article

Background: Mediastinal staging plays a critical role in guiding treatment decisions for non-small cell lung cancer (NSCLC). While mediastinoscopy has been the gold standard for assessing mediastinal lymph node involvement, endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has emerged as a minimally invasive alternative with comparable diagnostic accuracy. This systematic review evaluates the diagnostic performance, safety, cost-effectiveness, and feasibility of EBUS-TBNA versus mediastinoscopy for mediastinal staging. Methods: A systematic literature review was conducted in accordance with PRISMA guidelines, including searches in Medline, Scopus, EMBASE, and Cochrane databases for studies published from 2010 onwards. A total of 1542 studies were identified, and after removing duplicates and applying eligibility criteria, 100 studies were included for detailed analysis. The extracted data focused on sensitivity, specificity, complications, economic impact, and patient outcomes. Results: EBUS-TBNA demonstrated high sensitivity (85–94%) and specificity (~100%), making it an effective first-line modality for NSCLC staging. Mediastinoscopy remained highly specific (~100%) but exhibited slightly lower sensitivity (86–90%). EBUS-TBNA had a lower complication rate (~2%) and was more cost-effective, while mediastinoscopy provided larger biopsy samples, essential for molecular and histological analyses. The need for general anaesthesia, longer hospital stays, and increased procedural costs make mediastinoscopy less favourable as an initial approach. Combining both techniques in select cases enhanced overall staging accuracy, reducing false negatives and improving diagnostic confidence. Conclusions: EBUS-TBNA has become the preferred first-line mediastinal staging method due to its minimally invasive approach, high diagnostic accuracy, and lower cost. However, mediastinoscopy remains crucial in cases requiring posterior mediastinal node assessment or larger tissue samples. The integration of both techniques in a stepwise diagnostic strategy offers the highest accuracy while minimizing risks and costs. Given the lower hospitalization rates and economic benefits associated with EBUS-TBNA, its widespread adoption may contribute to more efficient resource utilization in healthcare systems. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling continuous patient monitoring, early diagnosis, and personalized treatments. However, the het-erogeneity of IoMT devices and the lack of standardized protocols introduce serious security vulnerabilities. To address these challenges, we propose a hybrid BiLSTM-DNN intrusion detection system, named HBiLD-IDS, that combines Bidirectional Long Short-Term Memory (BiLSTM) networks with Deep Neural Networks (DNNs), leveraging both temporal dependencies in network traffic and hierarchical feature extraction. The model is trained and evaluated on the CICIoMT2024 dataset, which accurately reflects the diversity of devices and attack vectors encountered in connected healthcare environments. The dataset undergoes rigorous preprocessing, including data cleaning, feature selection through correlation analysis and recursive elimination, and feature normalization. Compared to existing IDS models, our approach significantly enhances detection accuracy and generalization capacity in the face of complex and evolving attack patterns. Experimental results show that the proposed IDS model achieves a classification accuracy of 98.81% across 19 attack types confirming its robustness and scalability. This approach represents a promising solution for strengthening the security posture of IoMT networks against emerging cyber threats. Full article

Background: Cochlear implantation (CI) in pediatric patients with cochlear nerve deficiencies (CND) remains controversial due to a highly variable clinical population, lack of evidence-based guidelines, and mixed research findings. This study assessed current clinical perspectives and practices regarding CI candidacy in children with CND among hearing healthcare professionals in the USA. Methods: An anonymous 19-question online survey was distributed to CI clinicians nationwide. The survey assessed professional background, experience with aplasia and hypoplasia, and perspectives on CI versus auditory brainstem implant (ABI) candidacy, including imaging practices and outcome expectations. Both multiple-choice and open-ended responses were analyzed to identify trends and reasoning. Results: Seventy-two responses were analyzed. Most clinicians supported CI for hypoplasia (60.2%) and, to a lesser extent, for aplasia (41.7%), with audiologists more likely than neurotologists to favor CI. Respondents cited lower risk, accessibility, and the potential for benefit as reasons to attempt CI before ABI. However, many emphasized a case-by-case approach, incorporating imaging, electrophysiological testing, and family counseling. Only 22.2% considered structural factors the best predictors of CI success. Conclusions: Overall, hearing health professionals in the USA tend to favor CI as a first-line option, while acknowledging the limitations of current diagnostic tools and the importance of individualized, multidisciplinary decision-making in CI candidacy for children with CND. Findings reveal a high variability in clinical perspectives on CI implantation for pediatric aplasia and hypoplasia and a lack of clinical consensus, highlighting the need for more standardized assessment and imaging protocols to provide greater consistency across centers and enable the development of evidence-based guidelines. Full article

The proliferation of biometric technology across various domains including user identification, financial services, healthcare, security, law enforcement, and border control introduces convenience in user identity verification while necessitating robust protection mechanisms for sensitive biometric data. While chaos-based encryption systems offer promising solutions, many existing chaos-based encryption schemes exhibit inherent shortcomings including deterministic randomness and constrained key spaces, often failing to balance security robustness with computational efficiency. To address this, we propose a novel dual-layer cryptographic framework leveraging a four-dimensional (4D) Qi hyperchaotic system for protecting biometric templates and facilitating secure feature matching operations. The framework implements a two-tier encryption mechanism where each layer independently utilizes a Qi hyperchaotic system to generate unique encryption parameters, ensuring template-specific encryption patterns that enhance resistance against chosen-plaintext attacks. The framework performs dimensional normalization of input biometric templates, followed by image pixel shuffling to permutate pixel positions before applying dual-key encryption using the Qi hyperchaotic system and XOR diffusion operations. Templates remain encrypted in storage, with decryption occurring only during authentication processes, ensuring continuous security while enabling biometric verification. The proposed system’s framework demonstrates exceptional randomness properties, validated through comprehensive NIST Statistical Test Suite analysis, achieving statistical significance across all 15 tests with p-values consistently above 0.01 threshold. Comprehensive security analysis reveals outstanding metrics: entropy values exceeding 7.99 bits, a key space of ${10}^{320}$, negligible correlation coefficients (<${10}^{-2}$), and robust differential attack resistance with an NPCR of 99.60% and a UACI of 33.45%. Empirical evaluation, on standard CASIA Face and Iris databases, demonstrates practical computational efficiency, achieving average encryption times of 0.50913s per user template for 256 × 256 images. Comparative analysis against other state-of-the-art encryption schemes verifies the effectiveness and reliability of the proposed scheme and demonstrates our framework’s superior performance in both security metrics and computational efficiency. Our findings contribute to the advancement of biometric template protection methodologies, offering a balanced performance between security robustness and operational efficiency required in real-world deployment scenarios. Full article

The modified Rankin Scale (mRS) is a widely used outcome measure for assessing disability in stroke care; however, its administration is often affected by subjectivity and variability, leading to poor inter-rater reliability and inconsistent scoring. Originally designed for hospital discharge evaluations, the mRS has evolved into an outcome tool for disability assessment and clinical decision-making. Inconsistencies persist due to a lack of standardization and cognitive biases during its use. This paper presents design principles for creating a standardized clinical assessment tool (CAT) for the mRS, grounded in human–computer interaction (HCI) and cognitive engineering principles. Design principles were informed in part by an anonymous online survey conducted with clinicians across Canada to gain insights into current administration practices, opinions, and challenges of the mRS. The proposed design principles aim to reduce cognitive load, improve inter-rater reliability, and streamline the administration process of the mRS. By focusing on usability and standardization, the design principles seek to enhance scoring consistency and improve the overall reliability of clinical outcomes in stroke care and research. Developing a standardized CAT for the mRS represents a significant step toward improving the accuracy and consistency of stroke disability assessments. Future work will focus on real-world validation with healthcare stakeholders and exploring self-completed mRS assessments to further refine the tool. Full article

Background/Objectives: Traumatic brain injury (TBI), especially mild TBI (mTBI), is frequently caused by traffic accidents, falls, or sports injuries. Although computed tomography (CT) is the gold standard for diagnosis, overuse can lead to unnecessary radiation exposure, increased healthcare costs, and emergency department saturation. Blood-based biomarkers have emerged as potential tools to optimize CT scan use. This systematic review aims to evaluate recent evidence on the role of specific blood biomarkers in guiding CT decisions in patients with mTBI. Methods: A systematic search was conducted in the PubMed, Cochrane, and CINAHL databases for studies published between 2020 and 2024. Inclusion criteria focused on adult patients with mTBI evaluated using both CT imaging and at least one of the following biomarkers: glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and S100 calcium-binding protein B (S100B). After screening, six studies were included in the final review. Results: All included studies reported high sensitivity and negative predictive value for the selected biomarkers in detecting clinically relevant intracranial lesions. GFAP and UCH-L1, particularly in combination, consistently identified low-risk patients who could potentially forgo CT scans. While S100B also showed high sensitivity, discrepancies in cutoff values across studies highlighted the need for harmonization. Conclusions: Blood biomarkers such as GFAP, UCH-L1, and S100B demonstrate strong potential to reduce unnecessary CT imaging in mTBI by identifying patients at low risk of significant brain injury. Future research should focus on standardizing biomarker thresholds and validating protocols to support their integration into clinical practice guidelines. Full article

Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, pathogens, and clinical biomarkers with high sensitivity and specificity. We analyze technological innovations in cell-free protein synthesis optimization, preservation strategies, and field deployment methods that have enhanced sensitivity, and practical applicability. The integration of synthetic biology approaches has enabled complex signal processing, multiplexed detection, and novel sensor designs including riboswitches, split reporter systems, and metabolic sensing modules. Emerging materials such as supported lipid bilayers, hydrogels, and artificial cells are expanding biosensor capabilities through microcompartmentalization and electronic integration. Despite significant progress, challenges remain in standardization, sample interference mitigation, and cost reduction. Future opportunities include smartphone integration, enhanced preservation methods, and hybrid sensing platforms. Cell-free biosensors hold particular promise for point-of-care diagnostics in resource-limited settings, environmental monitoring applications, and food safety testing, representing essential tools for addressing global challenges in healthcare, environmental protection, and biosecurity. Full article

With the growing severity of environmental pollution, people are paying increasing attention to their health. However, naturally occurring wood with health benefits and applications in human healthcare is still scarce. Natural wood exhibits a limited negative oxygen ion release capacity, and this release has a short duration, failing to meet practical application requirements. This study innovatively developed a humidity-responsive, healthy wood material with a high negative oxygen ion release capacity based on fast-growing poplar. Through vacuum cyclic impregnation technology, hexagonal stone powder was infused into the pores of poplar wood, endowing it with the ability to continuously release negative oxygen ions. The healthy wood demonstrated a static average negative oxygen ion release rate of 537 ions/cm³ (peaking at 617 ions/cm³) and a dynamic average release rate of 3,170 ions/cm³ (peaking at 10,590 ions/cm³). The results showed that the particle size of hexagonal stone powder in suspension was influenced by the dispersants and dispersion processes. The composite dispersion process demonstrated optimal performance when using 0.5 wt% silane coupling agent γ-(methacryloxy)propyltrimethoxysilane (KH570), achieving the smallest particle size of 8.93 μm. The healthy wood demonstrated excellent impregnation performance, with a weight gain exceeding 14.61% and a liquid absorption rate surpassing 165.18%. The optimal impregnation cycle for vacuum circulation technology was determined to be six cycles, regardless of the type of dispersant. Compared with poplar wood, the hygroscopic swelling rate of healthy wood was lower, especially in PEG-treated samples, where the tangential, radial, longitudinal, and volumetric swelling rates decreased by 70.93%, 71.67%, 69.41%, and 71.35%, respectively. Combining hexagonal stone powder with fast-growing poplar wood can effectively enhance the release of negative oxygen ions. The static average release of negative oxygen ions from healthy wood is 1.44 times that of untreated hexagonal stone powder, and the dynamic release reaches 2 to 3 times the concentration of negative oxygen ions specified by national fresh air standards. The water-responsive mechanism revealed that negative oxygen ion release surged when ambient humidity exceeded 70%. This work proposes a sustainable and effective method to prepare healthy wood with permanent negative oxygen ion release capability. It demonstrates great potential for improving indoor air quality and enhancing human health. Full article

Vitamin D is the only vitamin that is conditionally essential, as it is synthesized from precursors after UV light exposure, whilst also being obtained from the diet. It has numerous health benefits, with deficiency becoming a major concern globally, such that dietary supplementation has more recently achieved vital importance to maintain satisfactory levels. In recent years, measurements made from blood have, therefore, become critical to determine the status of vitamin D levels in individuals and the larger population. Tests for vitamin D have routinely relied on laboratory analysis with sophisticated equipment, often being slow and costly, whilst rapid immunoassays have suffered from poor specificity and sensitivity. Here, we have evaluated a new rapid immunoassay test on the market (Rapi-D & IgLoo) to quickly and accurately measure vitamin D levels in small capillary blood specimens and compared this to measurements made using the standard laboratory method of liquid chromatography and mass spectrometry. Our results show that vitamin D can be measured very quickly and over a broad range using the new method, as well as correlate relatively well with standard laboratory testing; however, it cannot be fully relied upon currently to accurately diagnose deficiency or sufficiency in individuals. Our statistical and comparative analyses find that the rapid immunoassay with digital quantification significantly overestimates vitamin D levels, leading to diminished diagnosis of vitamin D deficiency. The speed and simplicity of the rapid method will likely provide advantages in various healthcare settings; however, further calibration of this rapid method and testing parameters for improving quantification of vitamin D from capillary blood specimens is required before integration of it into clinical decision-making pathways. Full article

Plant by-products have gained significant attention due to their rich content in bioactive compounds, which exhibit promising antioxidant, antimicrobial, and antitumor properties. In European countries, vegetable waste generation ranged from 35 to 78 kg per capita in 2022, highlighting both the scale of the challenge and the potential for valorization. This review provides an overview of key studies investigating the potential of plant residues in biomedicine, highlighting their possible contents of antioxidant compounds, their antimicrobial and antitumor properties, as well as their applications in dermocosmetics and nutraceuticals. However, despite their potential, several challenges must be addressed, such as the standardization of extraction protocols, as bioactive compound profiles can vary with plant source, processing conditions, and storage methods. Effective segregation and storage protocols for household organic waste also require optimization to ensure the quality and usability of plant by-products in biomedicine. Emerging 4.0 technologies could help to identify suitable plant by-products for biomedicine, streamlining their selection process for high-value applications. Additionally, the transition from in vitro studies to clinical trials is hindered by gaps in the understanding of Absorption, Distribution, Metabolism, and Excretion (ADME) properties, as well as interaction and toxicity profiles. Nonetheless, environmental education and societal participation are crucial to enabling circular bioeconomy strategies and sustainable biomedical innovation. Full article

Surgery remains a healthcare intervention with significant risks for patients. Novel technologies can now enhance the peri-operative workflow, with artificial intelligence (AI) and extended reality (XR) to assist with pre-operative planning. This review focuses on innovation in AI, XR and imaging for hepato-biliary surgery planning. The clinical challenges in hepato-biliary surgery arise from heterogeneity of clinical presentations, the need for multiple imaging modalities and highly variable local anatomy. AI-based models have been developed for risk prediction and multi-disciplinary tumor (MDT) board meetings. The future could involve an on-demand and highly accurate AI-powered decision tool for hepato-biliary surgery, assisting the surgeon to make the most informed decision on the treatment plan, conferring the best possible outcome for individual patients. Advances in AI can also be used to automate image interpretation and 3D modelling, enabling fast and accurate 3D reconstructions of patient anatomy. Surgical navigation systems utilizing XR are already in development, showing an early signal towards improved patient outcomes when used for hepato-biliary surgery. Live visualization of hepato-biliary anatomy in the operating theatre is likely to improve operative safety and performance. The technological advances in AI and XR provide new applications in pre-operative planning with potential for patient benefit. Their use in surgical simulation could accelerate learning curves for surgeons in training. Future research must focus on standardization of AI and XR study reporting, robust databases that are ethically and data protection-compliant, and development of inter-disciplinary tools for various healthcare applications and systems. Full article

Irradiation with ultraviolet light-emitting diodes (UV-LEDs) represents a promising method for viral inactivation, but a detailed understanding of the wavelength-dependent action spectra remains limited, particularly across different viral components. In this study, we established standardized UV action spectra for infectivity reduction in pathogenic viruses using a system equipped with interchangeable LEDs at 13 different peak wavelengths (250–365 nm). The reduction in viral infectivity induced by UV-LED exposure was strongly related to viral genome damage, whereas no significant degradation of viral structural proteins was detected. Peak virucidal efficiency was observed at 267–270 nm across all tested viruses, representing a slight shift from the traditionally expected 260 nm nucleic acid absorption peak. Enveloped RNA viruses, including influenza A virus, respiratory syncytial virus, and coronavirus, exhibited greater UV sensitivity than nonenveloped viruses such as feline calicivirus and adenovirus. These observations indicate that structural characteristics, such as the presence of an envelope and genome organization, influence UV susceptibility. The wavelength-specific action spectra established in this study provide critical data for optimizing UV-LED disinfection systems to achieve efficient viral inactivation while minimizing energy consumption in healthcare, food safety, and environmental sanitation. Full article

Background/Objectives: Sudden cardiac arrest (SCA) is a major global health concern with high mortality despite advances in resuscitation techniques. Achieving return of spontaneous circulation (ROSC) represents merely the initial step in the extensive rehabilitation journey. This review highlights the critical role of structured, multidisciplinary rehabilitation following ROSC, emphasizing the necessity of integrated physiotherapy, neurocognitive therapy, and psychosocial support to enhance quality of life and societal reintegration in survivors. Methods: This narrative review analyzed peer-reviewed literature from 2020–2025, sourced from databases such as PubMed, Scopus, Web of Science, and Google Scholar. Emphasis was on clinical trials, expert guidelines (e.g., European Resuscitation Council 2021, American Heart Association 2020), and high-impact journals, with systematic thematic analysis across rehabilitation phases. Results: The review confirms rehabilitation as essential in addressing Intensive Care Unit–acquired weakness, cognitive impairment, and post-intensive care syndrome. Early rehabilitation (0–7 days post-ROSC), focusing on parameter-guided mobilization and cognitive stimulation, significantly improves functional outcomes. Structured interdisciplinary interventions encompassing cardiopulmonary, neuromuscular, and cognitive domains effectively mitigate long-term disability, facilitating return to daily activities and employment. However, access disparities and insufficient randomized controlled trials limit evidence-based standardization. Discussion: Optimal recovery after SCA necessitates early and continuous interdisciplinary engagement, tailored to individual physiological and cognitive profiles. Persistent cognitive fatigue, executive dysfunction, and emotional instability remain significant barriers, underscoring the need for holistic and sustained rehabilitative approaches. Conclusions: Comprehensive, individualized rehabilitation following cardiac arrest is not supplementary but fundamental to meaningful recovery. Emphasizing early mobilization, neurocognitive therapy, family involvement, and structured social reintegration pathways is crucial. Addressing healthcare disparities and investing in rigorous randomized trials are imperative to achieving standardized, equitable, and outcome-oriented rehabilitation services globally. Full article