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 […]
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 […]
Impact of telehealth on health outcomes and quality of life in the older adults population: a systematic review
BackgroundThe rapid aging of populations poses major challenges to health and social care systems. Supporting older adults in managing chronic conditions while promoting independence and quality of life requires innovative approaches that extend beyond senior institutional care. Telehealth has emerged as a promising approach to enhance access, continuity, and patient engagement. However, evidence regarding its […]
Leveraging AI-based digital systems in psychological interventions: a research opinion
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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 […]
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 […]
Artificial intelligence-based remote monitoring for chronic heart failure: design and rationale of the SMART-CARE study
IntroductionChronic heart failure (CHF) is associated with frequent hospitalizations, poor quality of life, and high healthcare costs. Despite therapeutic progress, early recognition of clinical deterioration remains difficult. The SMART-CARE study investigates whether artificial intelligence (AI)-enabled remote monitoring using CE-certified wearable devices can reduce hospital admissions and improve patient outcomes in CHF.MethodsSMART-CARE is a prospective, multicenter, […]
US commission urges action as China’s biotech sector advances
A US congressional commission is escalating its warning that the US could soon be eclipsed by China in biotech, after lawmakers took up some of its recommendations earlier this year. In a report released early …
DiscoverDCP: A Data-Driven Approach for Construction of Disciplined Convex Programs via Symbolic Regression
arXiv:2512.15721v1 Announce Type: cross Abstract: We propose DiscoverDCP, a data-driven framework that integrates symbolic regression with the rule sets of Disciplined Convex Programming (DCP) to perform system identification. By enforcing that all discovered candidate model expressions adhere to DCP composition rules, we ensure that the output expressions are globally convex by construction, circumventing the computationally […]