ArticleActa neurochirurgica. Supplement2022
Machine Learning and Ethics.
Article in Acta neurochirurgica. Supplement, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Ethical and Regulatory Perception of Artificial Intelligence Among Dental Students: A Cross-Sectional Study.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Can we trust academic AI detective? Accuracy and limitations of AI-output detectors.Acta neurochirurgica · 2025Article
- Leveraging machine learning in nursing: innovations, challenges, and ethical insights.Frontiers in digital health · 2025Review
- The age of Artificial Intelligence in neurosurgical practice and educational paradigms - Considerations from the EANS Ethico-Legal and Young Neurosurgeons' committees.Brain & spine · 2025Article
- The clinical and ethical challenges of treating comatose patients following severe brain injury.Acta neurochirurgica · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
When new technology is introduced into healthcare, novel ethical dilemmas arise in the human-machine interface. As artificial intelligence (AI), machine learning (ML) and big data can exhaust human oversight and memory capacity, this will give rise to many of these new dilemmas.Technology has little if any ethical status but is inevitably interwoven with human activity and thus may serve to allow qualitative and quantitative disruption of human performance and interaction. We argue that personal integrity, justice of resource allocation and accountability of moral agency comprise three themes that characterize ethical dilemmas that arise with development and application of AI. These themes are important to address in parallel to further evolution of AI in health care for ethical practice of healthcare.
Indexed as
Identifiers
34862548What 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.