SynthesisBMC medical ethics2026
"First, do no harm" in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence: A systematic literature review.
Synthesis in BMC medical ethics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Beyond Algorithmic Oversight: Internal Morality of Medicine and Meaningful Human Control in AI-Assisted Care.Healthcare (Basel, Switzerland) · 2026Article
- A maturity model framework for federated networks of trusted research environments.Frontiers in digital health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundThis systematic review aims to synthesize the current knowledge about the applications and challenges of Artificial Intelligence (AI) technologies in healthcare, while evaluating the extent to which the European Union (EU) AI Act and the European Health Data Space (EHDS) contribute to ensuring responsible, secure, and ethically sound adoption of AI in clinical practice.
methodsThis review adheres to the guidelines set by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and has also been registered in PROSPERO. The PubMed®, Web of Science™, Scopus and ScienceDirect® databases were used as scientific search strategy. In addition, records identified through other sources (grey literature) were also assessed for eligibility and included. All studies published between 2020 and 2024 about the application of AI and its regulation and ethical implications, particularly in healthcare, were included. Eligible studies were assessed for potential risk of bias during data extraction and quality evaluation screening.
resultsA total of 76 studies were included. Although AI technologies have several applications in the healthcare sector such as disease diagnosis, treatment, clinical data management, automated surgery, remote health monitoring, elderly patient care and/ or biomedical research, important ethical issues are raised when using AI, namely data privacy, safety, lack of transparency, explainability, trust and potential biases.
conclusionsA proper application and compliance with established ethical principles, and legal regulations such as the EU AI Act and the EHDS are fundamental to ensure a responsible, safe, sustainable and trustworthy use of AI in healthcare.
Indexed as
Identifiers
What Socratic 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 Socratic graph.