ArticleEuropean heart journal. Digital health2026
Total product lifecycle regulatory considerations and recommendations for generative AI-enabled medical devices.
Article in European heart journal. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From assistance to autonomy: AI agent systems in cardiovascular medicine-a review of paradigms, architectures, and clinical translation.Frontiers in cardiovascular medicine · 2026Pooled it
- Artificial intelligence in clinical trials-state of the evidence, gaps, and next steps.EClinicalMedicine · 2026Review
- Clinical AI and Precision Medicine: Philosophical Questions About Labels, Disease, and Evidence.Journal of medical systems · 2026Article
- Implications of the new US AI framework in medicine.Communications medicine · 2026Article
- Evidence, use cases, and implementation safeguards of large language models in primary care.Communications medicine · 2026Review
- Validation is not enough: Longitudinal evidence of post-deployment fragility in clinical AI systems.PLOS digital health · 2026Article
- Advancing health equity in proactive health management: from data underrepresentation and algorithmic bias to a closed-loop governance framework.Frontiers in public health · 2026Review
- A generative AI multi-agent framework with integrated XAI governance for cancer diagnostics: from multi-omics interpretation to lifestyle risk stratification.Frontiers in systems biology · 2026Review
- Transforming Cardio-Oncology Care Through AI-Driven Large Language Model Systems: A Roadmap for Future Implementation.JACC. Advances · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As generative artificial intelligence (GenAI) emerges within the healthcare ecosystem, the regulatory environment surrounding these technologies remains fragmented. Importantly, GenAI in healthcare requires adapting the established Total Product Lifecycle (TPLC) paradigm to non-deterministic, rapidly evolving software, translating it into concrete steps for pre-market evaluation, change controls, and post-market performance monitoring to keep devices safe and effective as they change. This manuscript elucidates the need for developers, healthcare providers, and clinicians to engage proactively with regulatory compliance during the development and deployment phases of genAI-enabled medical devices. By understanding the nuances of national and international regulations, stakeholders can better navigate the unique risks of the evolving landscape of GenAI-enabled medical devices, while ensuring patient safety and outcome optimisation. Finally, this manuscript highlights the importance of the TPLC approach in managing the risks associated with GenAI-enabled technologies, offering recommendations for improving health outcomes and balancing the interests of various stakeholders.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.