ReviewKidney diseases (Basel, Switzerland)2019
Societal Issues Concerning the Application of Artificial Intelligence in Medicine.
Review in Kidney diseases (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
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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.
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Who cites it
38 citing papers in PubMed.
- Health economics evaluation of artificial intelligence in the field of oncology: a scoping review.Health economics review · 2026Review
- ChatGPT Versus DeepSeek for Breast Cancer Information Retrieval: Quantitative Comparative Study.JMIR cancer · 2026Article
- Hierarchy and hope: Exploring AI's role in medicine through a thematic analysis of online discourse.PLOS digital health · 2026Article
- Exploring Facilitators and Barriers for Personalized Dietary Incentives Among Online Shoppers at Cardiovascular Risk and Key Informants to Inform an Automated Shopping Platform.Journal of nutrition education and behavior · 2025Article
- Evaluating the Efficacy of Large Language Models in Generating Medical Documentation: A Comparative Study of ChatGPT-4, ChatGPT-4o, and Claude.Aesthetic plastic surgery · 2025Article
- Article
- Exploring Stakeholders' Perceptions of Using Digital Health Technologies to Improve the Conservative Treatment of Adolescent Idiopathic Scoliosis: Qualitative Study.Journal of medical Internet research · 2025Article
- FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare.BMJ (Clinical research ed.) · 2025Article
- Societal factors influencing the implementation of AI-driven technologies in (smart) hospitals.PloS one · 2025Article
- Artificial Intelligence in Medicine and Imaging Applications.Current pharmaceutical design · 2025Review
- Perceptions of health data commodification in AI-driven healthcare systems in Saudi Arabia.Frontiers in artificial intelligence · 2025Article
- Frameworks for procurement, integration, monitoring, and evaluation of artificial intelligence tools in clinical settings: A systematic review.PLOS digital health · 2024Article
- Towards the adoption of quantitative computed tomography in the management of interstitial lung disease.European respiratory review : an official journal of the European Respiratory Society · 2024Review
- Artificial intelligence integration in the drug lifecycle and in regulatory science: policy implications, challenges and opportunities.Frontiers in pharmacology · 2024Article
- Predictive modeling of biomedical temporal data in healthcare applications: review and future directions.Frontiers in physiology · 2024Review
- Multiomic Investigations into Lung Health and Disease.Microorganisms · 2023Review
- Machine Learning in Laboratory Medicine: Recommendations of the IFCC Working Group.Clinical chemistry · 2023Article
- Exploring computer-based imaging analysis in interstitial lung disease: opportunities and challenges.ERJ open research · 2023Review
- Real-World Implementation of Artificial Intelligence/Machine Learning for Managing Surgical Spine Patients at 2 Academic Health Care Systems.International journal of spine surgery · 2023Article
- An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models.Neural computing & applications · 2023Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMedicine is becoming an increasingly data-centred discipline and, beyond classical statistical approaches, artificial intelligence (AI) and, in particular, machine learning (ML) are attracting much interest for the analysis of medical data. It has been argued that AI is experiencing a fast process of commodification. This characterization correctly reflects the current process of SUMMARY AND KEY MESSAGES: AI and ML are attracting much interest from the medical community as key approaches to knowledge extraction from data. These approaches are increasingly colonizing ambits of social impact, such as medicine and healthcare. Issues of social relevance with an impact on medicine and healthcare include (although they are not limited to) fairness, explainability, privacy, ethics and legislation.
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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.