ReviewDer Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen2022
[Ethical, legal and social implications in the use of artificial intelligence-based technologies in surgery : Principles, implementation and importance for the user].
Review in Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Intraoperative application of mixed and augmented reality for digital surgery: a systematic review of ethical issues.Frontiers in surgery · 2024Pooled it
- The Role of AI in Shaping Medical Education: Insights from an Umbrella Review of Review Studies.Journal of advances in medical education & professionalism · 2025Review
- Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education.Medical science educator · 2023Article
- Assessment of Performance, Interpretability, and Explainability in Artificial Intelligence-Based Health Technologies: What Healthcare Stakeholders Need to Know.Mayo Clinic proceedings. Digital health · 2023Review
- Human visual explanations mitigate bias in AI-based assessment of surgeon skills.NPJ digital medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ethical, legal and social aspects are gaining increasingly more attention in the development and during the initial clinical application of medical devices. The introduction of elements of artificial intelligence (AI) and systems which are using AI makes this already complex topic even more challenging. The introduction of so-called dynamic AI or dynamic machine learning (ML) algorithms in this respect represents a turning point. Unlike conventional medical devices, the development of systems using dynamic AI is not yet complete at the beginning of the clinical application. The aim of a dynamic AI system is to continuously improve through practical use and by the processing of usage data. This continuous evolution, along with the lack of transparency regarding internal work processes, could make it difficult to understand the underlying rationale for the assessments made by the algorithms. This aspect affects the acceptance of the technology both by clinicians and patients and furthermore questions the autonomy of patients and clinicians in the course of the treatment process. A way out of this ethical and regulatory dilemma must urgently be found and will require extreme efforts from all stakeholders. At present, no consensual solution is apparent. What is quite certain, however, is that users, i.e. in concrete terms surgeons, must play a much more active role than they have done in the past when dealing with AI-based medical devices and should prepare themselves to actively accompany the software life cycle of AI technologies.
Indexed as
Identifiers
35147728What 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.