ReviewYearbook of medical informatics2022
A Literature Review on Ethics for AI in Biomedical Research and Biobanking.
Review in Yearbook of medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- The Role of AI in Shaping Medical Education: Insights from an Umbrella Review of Review Studies.Journal of advances in medical education & professionalism · 2025Review
- Psychiatry in the age of AI: transforming theory, practice, and medical education.Frontiers in public health · 2025Review
- Ethical theories, governance models, and strategic frameworks for responsible AI adoption and organizational success.Frontiers in artificial intelligence · 2025Review
- Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.Molecules (Basel, Switzerland) · 2024Review
- Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024Review
- Artificial Intelligence Needs Data: Challenges Accessing Italian Databases to Train AI.Asian bioethics review · 2024Article
- Article
- Do biobanks need pharmacists? Support of pharmacy students to biobanking of human biological material for pharmaceutical research and development.Frontiers in pharmacology · 2024Article
- The Ubuntu Way: Ensuring Ethical AI Integration in Health Research.Wellcome open research · 2024Review
- Unlocking the potential of big data and AI in medicine: insights from biobanking.Frontiers in medicine · 2024Article
- Revolutionizing Cancer Research: The Impact of Artificial Intelligence in Digital Biobanking.Journal of personalized medicine · 2023Review
- Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education.Medical science educator · 2023Article
- Digital Biobanking and Big Data as a New Research Tool: A Position Paper.Healthcare (Basel, Switzerland) · 2023Article
- Inclusive Digital Health.Yearbook of medical informatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial Intelligence (AI) is becoming more and more important especially in datacentric fields, such as biomedical research and biobanking. However, AI does not only offer advantages and promising benefits, but brings about also ethical risks and perils. In recent years, there has been growing interest in AI ethics, as reflected by a huge number of (scientific) literature dealing with the topic of AI ethics. The main objectives of this review are: (1) to provide an overview about important (upcoming) AI ethics regulations and international recommendations as well as available AI ethics tools and frameworks relevant to biomedical research, (2) to identify what AI ethics can learn from findings in ethics of traditional biomedical research - in particular looking at ethics in the domain of biobanking, and (3) to provide an overview about the main research questions in the field of AI ethics in biomedical research.
methodsWe adopted a modified thematic review approach focused on understanding AI ethics aspects relevant to biomedical research. For this review, four scientific literature databases at the cross-section of medical, technical, and ethics science literature were queried: PubMed, BMC Medical Ethics, IEEE Xplore, and Google Scholar. In addition, a grey literature search was conducted to identify current trends in legislation and standardization.
resultsMore than 2,500 potentially relevant publications were retrieved through the initial search and 57 documents were included in the final review. The review found many documents describing high-level principles of AI ethics, and some publications describing approaches for making AI ethics more actionable and bridging the principles-to-practice gap. Also, some ongoing regulatory and standardization initiatives related to AI ethics were identified. It was found that ethical aspects of AI implementation in biobanks are often like those in biomedical research, for example with regards to handling big data or tackling informed consent. The review revealed current 'hot' topics in AI ethics related to biomedical research. Furthermore, several published tools and methods aiming to support practical implementation of AI ethics, as well as tools and frameworks specifically addressing complete and transparent reporting of biomedical studies involving AI are described in the review results.
conclusionsThe review results provide a practically useful overview of research strands as well as regulations, guidelines, and tools regarding AI ethics in biomedical research. Furthermore, the review results show the need for an ethical-mindful and balanced approach to AI in biomedical research, and specifically reveal the need for AI ethics research focused on understanding and resolving practical problems arising from the use of AI in science and society.
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.