Quantum-SpinalNet: a hybrid deep learning approach for mammographic breast cancer detection

IntroductionBreast cancer diagnosis in mammograms remains challenging due to limitations in preprocessing, accurate differentiation of benign and malignant cases, and precise tumor segmentation.MethodsWe propose Quantum-SpinalNet, a hybrid deep learning model combining Swin ResUNet3+ for tumor segmentation with a Deep Quantum Neural Network (DQNN) and SpinalNet for classification. Preprocessing involves CEAMF-based denoising, Z-score normalization, and context-aware […]

Maccabi-RED, mHealth innovation in community emergency care: a 4-year analysis of adoption patterns and impact on healthcare utilization

IntroductionEmergency department overcrowding due to non-urgent visits places a considerable burden on the healthcare system. Mobile health (mHealth) technologies offer potential solutions by providing community-based alternatives for emergency care.MethodsIn this study, we analyzed 4 years of implementation data from Maccabi-RED, a smartphone app-based emergency care service launched in 2019 by Israel’s second-largest healthcare maintenance organization. […]

Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings—a scoping review

BackgroundArtificial intelligence (AI) has the potential to revolutionize healthcare delivery in low- and middle-income countries (LMICs), yet its rapid adoption raises complex ethical, regulatory, and implementation challenges. This review investigates these barriers and identifies emerging strategies that support equitable and inclusive AI deployment in resource-limited settings.MethodsFollowing the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines, a […]

ChatGPT for diabetes education: potential, accuracy, and accessibility in patient support

BackgroundDiabetes mellitus is a chronic metabolic disease with rising global prevalence. Adequate patient education is essential to encourage self-management and reduce complications. Artificial intelligence applications such as ChatGPT have emerged as potential supplementary resources for patient education alongside the broader integration of technology in healthcare.MethodsA cross-sectional evaluation was conducted using ten frequently asked questions (FAQs) […]

Co-designing animated videos to explain large language models and their use in healthcare and research

IntroductionThe increasing development of large language models (LLM) in healthcare research is taking place without patient and public involvement and engagement (PPIE). Part of the challenge is the lack of accessible educational resources to promote literacy around LLMs.MethodsWe employed a co-design approach with 6 PPIE contributors from Tower Hamlets, London to develop educational animations about […]

Exploring plausible futures for artificial intelligence in rural healthcare: insights from participatory foresight methods

BackgroundArtificial intelligence (AI) has the potential to transform rural healthcare delivery through automated monitoring, personalised care, and virtual support. Yet the future pathways for AI in rural contexts remain underexplored. Most AI applications are developed in urban-centric environments with limited consideration for infrastructure constraints, workforce realities, and sociocultural dynamics that shape rural healthcare delivery.MethodsThis study […]

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 […]

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