Advancing the adoption of oncology decision support tools in Europe: insights from CAN.HEAL

Effective cancer care increasingly depends on digital decision support tools (DSTs) to interpret complex clinical, molecular, and genomic data and guide personalised treatment decisions. However, the oncology DST (oncDST) landscape remains fragmented, with limited interoperability, inconsistent standards, and uneven clinical adoption across healthcare systems. This fragmentation hinders routine clinical use and impedes the demonstration of […]

Early Type 2 diabetes risk prediction using explainable machine learning in a two-stage approach

BackgroundDiabetes is a chronic disease characterized by elevated blood glucose levels. Without early detection and proper management, it can lead to serious complications and increase healthcare costs. Its global prevalence is rising, with many cases remaining undiagnosed. In this study, we developed an explainable machine learning model using a two-stage approach for predicting diabetes.MethodsFive machine […]

Cybersecurity breaches in medical devices: analyzing FDA safety communications in response to patient security concerns

IntroductionThe increasing integration of connected medical devices and internet of things (IoT) technologies in healthcare has significantly improved patient care and operational efficiency. However, this rapid digital transformation has also introduced serious cybersecurity vulnerabilities in medical devices, posing risks to patient safety and sensitive health data. Cybersecurity threats can allow unauthorized remote access to devices, […]

Ethical examination of AI coaches: privacy, bias, and responsibility

The integration of artificial intelligence (AI) into sports, particularly through AI-driven coaching systems, marks a transformative advancement with the potential to revolutionize personalized training. AI coaches can create customized, data-driven training programs designed to optimize athletic performance. However, this technological progress also brings with it significant ethical concerns, including privacy violations, data biases, and ambiguous […]

Translating behavioral interventions into virtual reality: the Transcend Framework for immersive health design

Virtual Reality (VR) has evolved from entertainment to a versatile platform for clinical and public health innovation. In medicine, VR supports pain management, rehabilitation, and cognitive training, and shows growing promise for addressing chronic diseases linked to modifiable risk factors. To support this expansion, we introduce the Transcend Framework, the Translational Engineering of Behavioral Interventions […]

Assessing ChatGPT vs. evidence-based online responses for polycystic ovary syndrome self-management and education: an international cross-sectional blinded survey of healthcare professionals

Artificial intelligence (AI)-powered large language models, such as ChatGPT, are increasingly used by the public for health information. The reliability of such novel AI-tools in providing credible polycystic ovary syndrome (PCOS) information/advice requires investigation. Healthcare professionals involved in PCOS care (n = 43 from 14 countries) used a 5-point Likert scale to evaluate ChatGPT-generated responses to frequently […]

Evaluating privacy leakages in LLM-driven ambient clinical documentation

IntroductionAutomated documentation tools are being rapidly adopted in healthcare and clinical workflows. Among these are AI-enabled ambient scribing products, which transcribe conversations between patients and healthcare providers, then produce clinical records using automatic speech recognition (ASR) and generative AI such as Large Language Models (LLMs). While research suggests these technologies can reduce clinical burden, safe […]

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