ArticleDigital health
Exploring artificial intelligence for healthcare from the health professionals' perspective: The case of limited resource settings.
Article in Digital health. 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
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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
2 citing papers in PubMed.
- Mapping National Governance of AI for Health: Protocol for a Global Scoping Review.JMIR research protocols · 2026Article
- Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Although artificial intelligence (AI) can boost clinical decision-making, personalize patient treatment, and advance the global health sectors, there are unique implementation challenges and considerations in developing countries. The perceptions, attitudes, and behavioral factors among the users are limitedly identified in Ethiopia. Objective: This study aimed to explore AI in healthcare from the perspectives of health professionals in a resource-limited setting. Methods: We employed a cross-sectional descriptive study including 404 health professionals. Data were collected using a self-structured questionnaire. A simple random sampling technique was applied. We used SPSS to analyze data. Tables and graphs were used to present the findings. Results: A 95.7% response rate was reported. The mean age of the respondents was 32.57 ± 5.34 SD. Almost 254 (62.9%) of the participants were Bachelors of Science degree holders. Nearly 156 (38.6%) of the participants were medical doctors. More than 50% (52.2%) of them said AI would be applicable for diagnosis and treatment purposes in healthcare organizations. This study identified that a favorable attitude, good knowledge, and formal training regarding AI technologies would foster clinical decision-making practices more efficiently and accurately. Similarly, our study also identified the potential barriers to AI technologies in healthcare such as ethical issues, privacy and security of patient data were some to mention. Conclusions: Our study revealed that positive attitude, good knowledge, and formal training are crucial to advance healthcare using AI technologies. In addition, this study identified self-reported AI concerns of the participants such as; privacy and security of data, ethical issues, and accuracy of AI systems. Attention could be given to overcome the barriers of AI systems in the health system. Providing training, allocating time to practice AI tools, incorporating AI courses in the curricula of medical education, and improving knowledge can further the usage of AI systems in healthcare settings.
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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.