Over the past decade, digital twins (DTs) have evolved from an engineering metaphor into a powerful paradigm for healthcare innovation. By dynamically linking physical and digital representations of patients, devices, and clinical processes, DTs enable continuous learning systems where data, knowledge, and decision-making converge. This transformation goes far beyond simulation: it redefines how we understand, […]
Deep learning-based beat-to-beat delineation of heart sounds and fiducial points in seismocardiography
IntroductionThe application of deep learning methods in automatic delineation of fiducial points in seismocardiography (SCG) on a beat-to-beat basis provides the possibility of obtaining a novel and comprehensive approach to assess and monitor myocardial mechanics and hemodynamic status. Therefore, the aim of this study was to develop an adaptive and data-driven algorithm for automatic delineation […]
Artificial intelligence in epidemic watch: revolutionizing infectious diseases surveillance
Artificial intelligence is undoubtedly emerging, and its various manifestations in technology are widely and deeply embedded in our communities. That is what obliges its mindful and skillful use and utilization, especially for infectious disease prevention. Over 1 million people are affected by infectious diseases, and the whole globe is carrying a huge burden of DALYs […]
Cost-effectiveness analysis of AI-assisted chest X-ray interpretation tools for TB screening: a rapid HTA
BackgroundEarly diagnosis remains one of the major barriers to treating and managing tuberculosis (TB). Artificial intelligence (AI) has increased in importance worldwide and has been employed in the context of tuberculosis screening. This study assessed whether newer AI-assisted technologies provide cost-effective benefits for the diagnosis of pulmonary tuberculosis in resource-limited settings.MethodsThis retrospective study analyzed secondary […]
Uncovering bias and variability in how large language models attribute cardiovascular risk
Large language models (LLMs) are used increasingly in medicine, but their decision-making in cardiovascular risk attribution remains underexplored. This pilot study examined how an LLM apportioned relative cardiovascular risk across different demographic and clinical domains. A structured prompt set across six domains was developed, across general cardiovascular risk, body mass index (BMI), diabetes, depression, smoking, […]
Correction: Improvements in physical activity and depression symptoms: an observational study of users of a multi-modal digital mental health platform
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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 […]
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, […]
Editorial: AI for health behavior change
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Digitally supported interprofessional interaction in healthcare—a scoping review
BackgroundThe increasing complexity of patient care and workforce shortages in healthcare systems necessitate improved interprofessional interaction. Digital technologies offer promising solutions to facilitate such interaction across healthcare settings.ObjectivesThis scoping review aimed to identify, categorize, and assess digital technologies that support interprofessional interaction among healthcare professionals, using the NASSS framework to evaluate their implementation context and […]