ArticleCureus2025
Ethical and Practical Dimensions of Artificial Intelligence (AI) in Healthcare: A Comprehensive Study of Professional Perceptions.
Article in Cureus, 2025. 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.
- Healthcare professionals show high AI enthusiasm but limited knowledge: A cross-sectional study.PLOS digital health · 2026Article
- Artificial Intelligence in Health Professions Education: Qualitative Study of Student Experiences.Journal of medical Internet research · 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
No grant is acknowledged in the PubMed record.
Abstract
Introduction Artificial intelligence (AI) transforms medicine by enhancing diagnoses, treatments, resource management, and personalized treatment plans. However, it poses ethical and legal challenges, such as data privacy and equitable access to its benefits. This study seeks to understand healthcare professionals' perceptions of AI regulation in a Costa Rican hospital and analyze the alignment of Latin American regulations with local realities. Methods The research is qualitative, descriptive, and cross-sectional, focusing on AI guidelines and laws in health at both international and national levels. The sample includes healthcare professionals from a private hospital in Costa Rica. Two instruments were used: a documentary review and an online survey. Data analysis was performed using descriptive and correlational statistics with RStudio (R Foundation for Statistical Computing, Vienna, Austria (https://www.R-project.org/)). Results Eighty healthcare professionals participated in the study. Findings revealed that most exhibited moderate familiarity with AI while underscoring the critical need for robust governance frameworks to navigate the ethical and regulatory complexities surrounding its implementation. Notably, no significant correlation emerged between AI familiarity and demographic factors. Limitations of this study include its focus on a single hospital and the heterogeneous regulatory landscape across Latin American countries. Conclusions The study reveals that the integration of AI in healthcare is promising but complex, requiring a multidimensional approach that includes technical, ethical, and social aspects. Healthcare professionals in Costa Rica show a favorable disposition towards AI, recognizing its potential to improve healthcare, although they also highlight concerns about data privacy, security, and ethics.
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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.