BackgroundPoor access to antenatal care (ANC), skilled delivery, and postnatal checks within 48 h of delivery are linked to adverse pregnancy outcomes. In Kenya, unequal use of these services has caused significant regional disparities, with 15 out of 47 counties being high priority.ObjectivesTo evaluate the effectiveness of a digital health solution to improve maternal and newborn […]
Implementation and outcomes of a digital onboarding taskforce in the acute care setting
IntroductionUse of digital health technology can improve patient health outcomes; however, not all patients have the knowledge and skills to download a health app and access a patient portal. Providing digital onboarding support to hospitalized patients has potential to overcome some barriers to accessing needed education in the community, including both having the time and […]
One digital health through wearables: a viewpoint on human–pet integration towards Healthcare 5.0
Wearable technologies mark a transition in healthcare evolution, from paternalistic (Healthcare 1.0) to reactive (Healthcare 2.0), proactive (Healthcare 3.0), and data-integrated care (Healthcare 4.0). The next stage, Healthcare 5.0, envisions the seamless integration of human and pet health data, fostering a more holistic approach to disease prevention and management. In this viewpoint, we explore the […]
AI/ML driven prediction of COPD exacerbations and readmissions: a systematic review and meta-analysis
BackgroundChronic obstructive pulmonary disease (COPD) exacerbations and hospital readmissions are major drivers of morbidity, mortality, and healthcare costs. Artificial intelligence and machine learning (AI/ML) approaches have been applied to predict these events, but their pooled performance and methodological rigor remain unclear.MethodsFollowing PRISMA 2020 guidelines, we conducted a systematic review and meta-analysis of peer-reviewed studies developing […]
ScolioClass: data-driven development of a new classification tool to evaluate adolescent idiopathic scoliosis optically diagnosed
Adolescent idiopathic scoliosis (AIS) is traditionally assessed and classified using radiographic methods that rely on Cobb angle measurements and qualitative curve modifiers, exposing patients to repeated radiation and offering limited sensitivity to subtle three-dimensional (3D) deformities. We developed ScolioClass, a non-invasive, data-driven classification tool that harnesses 3D optical surface scanning and continuous indices, capturing curvature […]
Leveraging AI-based digital systems in psychological interventions: a research opinion
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AI Wrapped: The 14 AI terms you couldn’t avoid in 2025
If the past 12 months have taught us anything, it’s that the AI hype train is showing no signs of slowing. It’s hard to believe that at the beginning of the year, DeepSeek had yet to turn the entire industry on its head, Meta was better known for trying (and failing) to make the metaverse […]
PCdare software registers 3D back surface with biplanar radiographs: application to patients with scoliosis
Optical 3D surface scanning is used increasingly to assess spinal deformity of patients with scoliosis. However, approaches based on optical 3D scanning often underestimate the spinal deformity. To improve the accuracy of such estimates, deeper understanding is required of scoliosis and its effect on the back shape. We present the PCdare research software which registers […]
FEM-Bench: A Structured Scientific Reasoning Benchmark for Evaluating Code-Generating LLMs
arXiv:2512.20732v1 Announce Type: cross Abstract: As LLMs advance their reasoning capabilities about the physical world, the absence of rigorous benchmarks for evaluating their ability to generate scientifically valid physical models has become a critical gap. Computational mechanics, which develops and applies mathematical models and numerical methods to predict the behavior of physical systems under forces, […]
Forward Only Learning for Orthogonal Neural Networks of any Depth
arXiv:2512.20668v1 Announce Type: cross Abstract: Backpropagation is still the de facto algorithm used today to train neural networks. With the exponential growth of recent architectures, the computational cost of this algorithm also becomes a burden. The recent PEPITA and forward-only frameworks have proposed promising alternatives, but they failed to scale up to a handful of […]