Artificial intelligence (AI) can offer individualized dietary guidance based on multimodal data collected from various sources, including wearable sensors, high-dimensional multiomics and biomarker analyses, behavioral tracking, and self-reported dietary intake, enabling the emergence of precision nutrition. However, the predictive power and fairness of these models rely on the quality of the data inputs, and measurement […]
Determinants of technology adoption among healthcare professionals at Mogadishu hospitals using an extended UTAUT model
The study used the expanded Unified Theory of Acceptance and usage of Technology (UTAUT) to identify the variables influencing the usage of technology by medical staff in hospitals in Mogadishu. This study aimed to identify the key factors influencing technology usage among hospital staff in Mogadishu, Somalia, using an expanded Unified Theory of Acceptance and […]
Designing and evaluating large language model-enabled clinical decision support for heart failure: a modular and risk-tiered framework
Heart failure (HF) care requires repeated decisions across suspected disease, diagnostic confirmation, phenotyping, guideline-directed medical therapy, device consideration, worsening HF, transition care, and advanced HF planning. Large language models (LLMs) may support this work by synthesizing structured and unstructured electronic health record data, retrieving current evidence, and presenting patient-specific reasoning. However, an HF-specific LLM clinical […]
Meta-analyses of randomized controlled trials assessing the effect of digital tools on step count and moderate-to-vigorous physical activity in healthy children and adolescents
BackgroundDigital tools can influence young people’s physical activity both positively and negatively. This meta-analysis (MA) aims to determine whether global interventions based on the use of digital tools are effective in increasing step count and moderate-to-vigorous physical activity (MVPA) among healthy school-aged children.MethodsThis MA builds upon a previous umbrella review that identified 43 randomized controlled […]
Computational modelling for personalized transcatheter aortic valve replacement planning: a systematic review of complications and decision support
Patient-specific digital simulation is emerging as a tool to support personalized planning of transcatheter aortic valve replacement (TAVR), particularly as the procedure expands to younger, lower-risk patients, and more complex anatomies. Despite procedural advances, complications such as paravalvular leak, conduction disturbances, coronary obstruction, and aortic injury remain important determinants of outcome. Current pre-procedural planning relies […]
Digital phenotyping of affect and stress in emerging adults
BackgroundDepression is highly heterogeneous and difficult to monitor or predict in daily life. One strategy for monitoring depressive symptoms is digital phenotyping, the real-time tracking of behaviors via personal devices. Digital phenotyping may be especially useful for predicting mood in emerging adults, a developmental period characterized by heightened rates of depression and smartphone use. However, […]
Digital marketing of e-cigarettes in Southeast Asia: a neglected digital health and platform governance challenge for youth protection
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Healthcare professionals’ perspectives on usefulness, acceptability and implementation conditions of socially assistive robots in France: a cross-sectional survey and cluster analysis
IntroductionIn healthcare, socially assistive robots are increasingly used for logistical, assistive, and psychosocial purposes, raising ethical, social, and organizational questions. In these contexts, professionals’ acceptability varies by use case, perceived risk, and care setting. Understanding how healthcare professionals evaluate these technologies is essential for anticipating their large-scale integration into health systems and its implications for […]
Editorial: Advances in generative artificial intelligence for mental health
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Feasibility of weekly patient-reported symptom monitoring using patients’ own smartphones in outpatient cancer chemotherapy: the SMART-PRO study
Electronic patient-reported outcome (ePRO) systems using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) can improve symptom monitoring, but the feasibility of implementing such systems with a bring-your-own-device (BYOD) approach in routine oncology practice, particularly among older adults, is not well established. We conducted a single-arm prospective observational study in […]
Voice disorders classification using machine learning: a scoping review
ObjectivesThis review aims to identify the key barriers to clinical application of Machine Learning (ML) in multi-class voice disorder classification.DesignScoping Review.MethodsA comprehensive scoping review of research published between 2013 and May 2025 in seven clinical and engineering databases was conducted. Articles that applied ML techniques to classify voice disorders were examined, excluding publications limited to […]
Evaluating artificial intelligence large language models in dental education: a cross-sectional survey on usage, perceptions, and integration at a U.S. dental school
IntroductionThe adoption of artificial intelligence (AI) in higher education presents opportunities and challenges for dental education. This study explores the use of Large Language Model (LLM) based AI tools, including ChatGPT and Grammarly AI, among faculty and students at the UTHealth School of Dentistry in Houston (UTSDH). This research assessed usage patterns, perceived benefits and […]