BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored. This study aimed to evaluate the psychometric properties of a previously validated nine-item scale measuring nurses’ knowledge and attitudes toward AI and to describe preliminary findings from primary healthcare centre […]
Bioethical considerations in deploying mobile mental health apps in LMIC settings: insights from the MITHRA pilot study in rural India
IntroductionIn India, untreated depression among women contributes significantly to morbidity and mortality, underscoring an urgent need for accessible and ethically grounded mental health interventions. Mobile health (mHealth) tools offer scalable solutions; however, their implementation in low- and middle-income country (LMIC) settings raises important bioethical considerations.MethodsThis study was conducted at the conclusion of a pilot randomized […]
Measuring and reducing surgical staff stress in a realistic operating room setting using EDA monitoring and smart hearing protection
BackgroundStress is a critical factor in the operating room (OR) and affects both the performance and well-being of surgical staff. Measuring and mitigating this stress can therefore improve patient safety and healthcare worker health.ObjectiveThis study aimed to evaluate the stress levels of OR staff in a simulated surgical setting using electrodermal activity (EDA) and to […]
A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction
The exponential growth of biomedical data necessitates advanced tools for efficient information extraction (IE) to support clinical decision-making and research. Large language models (LLMs) have emerged as transformative solutions, yet their application in healthcare raises critical trade-offs between open-source (OSS) and proprietary models. This review evaluates IE workflows such as named entity recognition, relation extraction, […]
From memorization to generalization: fine-tuning large language models for biomedical term-to-identifier normalization
IntroductionBiomedical data integration requires term-to-identifier normalization, the process of linking natural-language biomedical terms to standardized ontology codes so that extracted concepts become computable and interoperable. Although large language models perform well on clinical text summarization and concept extraction, they remain markedly less accurate at mapping ontology terms to their corresponding identifiers.MethodsWe examined the roles of […]
Structuring medication safety narratives: development and evaluation of the medication-related incident reports annotation scheme
IntroductionNarrative reports of medication-related incidents contain valuable information about the causes and consequences of errors, but their unstructured format limits systematic analysis. Although natural language processing (NLP) can convert narrative reports into structured data, few annotation schemes have been developed specifically for medication safety and validated using real-world healthcare incident data. This study aimed to […]
Use of digital patients in clinical simulation for nursing education: a scoping review protocol
IntroductionClinical simulation represents an emerging educational technology delivered through software-based platforms, accessible via computers or head-mounted displays. It is characterized as a partially immersive, screen-mediated experience in which learners are placed in simulated roles that require the execution of psychomotor actions, clinical decision-making, and interpersonal communication skills.Methods and analysisThis scoping review protocol follows the methodological […]
IoT-based health monitoring and social welfare access for Thailand’s older adults
IntroductionThailand’s population is shifting, with 20% aged 60 and over in 2022, leading to healthcare and social welfare challenges. Digital technologies, particularly those using IoT, may improve health outcomes for older adults but face hurdles due to low digital literacy and a digital divide between urban and rural areas. This study investigated the accessibility and […]
Influence of social media on cosmetic and gynecologic aesthetic decisions among women in Saudi Arabia
ObjectiveTo explore how social media influences cosmetic and gynecologic aesthetic decision-making among women in Saudi Arabia, with attention to behavioral, psychological, ethical, and cultural dimensions.MethodsA structured narrative review guided by SANRA principles was conducted using publications from 2018 to 2024 identified through PubMed, OpenAlex, and institutional repositories. Studies were screened thematically and synthesized using a […]
Deep learning for intracranial hemorrhage detection and classification in brain CT scans: a systematic review and hybrid model approach
BackgroundIntracranial hemorrhage (ICH) is a life-threatening medical emergency requiring rapid and accurate diagnosis. Non-contrast computed tomography (CT) remains the primary imaging modality for detecting acute hemorrhage. In recent years, machine learning (ML) and deep learning (DL) approaches have gained increasing attention for automated detection and classification of ICH and its subtypes. This systematic review aims […]
Federated learning for fair autism spectrum disorder screening across age-heterogeneous populations
IntroductionThe detection of Autism Spectrum Disorder (ASD) remains challenging due to the heterogeneity of behavioural manifestations, limited dataset availability, and strict privacy requirements. Conventional centralized machine learning approaches often suffer from overfitting and limited generalizability across different age groups. This study proposes a federated learning (FL) framework to enable collaborative ASD screening across children, adolescents, […]
Amplifying missing voices in healthcare research: an AI framework for co-production of PPIE
Patient and Public Involvement and Engagement (PPIE) is essential for high-quality healthcare research, yet significant challenges persist in achieving diverse input. Traditional PPIE panels can struggle with recruitment limitations, geographical constraints, and resource intensity, resulting in panels that may not reflect population diversity or lived experiences. In order to address these challenges, we developed Panelyze, […]