ReviewBMC medical education2023
Revolutionizing healthcare: the role of artificial intelligence in clinical practice.
Review in BMC medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07134374 (Investigation of the Relationship Between Nurses' Attitudes Toward Artificial Intelligence and Their Critical Thinking Dispositions), which is not on this map. Cited by 1,112 papers, 11 of them syntheses that pooled it.
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.
Investigation of the Relationship Between Nurses' Attitudes Toward Artificial Intelligence and Their Critical Thinking Dispositions
Who cites it
1,112 citing papers in PubMed, 11 syntheses or guidelines pooled it, 2,569 citations in OpenAlex.
- Artificial intelligence-powered renal pathology for glomerular disease classification: a systematic review and meta-analysis.Renal failure · 2026Pooled it
- Stakeholder Perspectives on the Integration of AI in Diabetes Care: Systematic Review of Qualitative Studies.Journal of medical Internet research · 2026Pooled it
- Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Preferences for AI-Enabled Health Care Technologies: Systematic Review of Discrete Choice Experiments and Reporting Quality Assessment Using the DIRECT Checklist.Journal of medical Internet research · 2026Pooled it
- Systematic Review on Artificial Intelligence in Rheumatology Practice: From Implementation Concerns to Imaging and Clinical Application.International journal of rheumatic diseases · 2026Pooled it
- The Emerging Roles of AI in Self-Directed Stress Management: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Artificial intelligence adoption in healthcare: a systematic review of implementation challenges and health services implications.BMC health services research · 2026Pooled it
- P300 Event-Related Potentials as Cognitive Biomarkers in Neurological and Neuropsychiatric Disorders: A Systematic Review.Revista de neurologia · 2026Pooled it
- Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Artificial Intelligence for Predicting Treatment Response in Patients With Anxiety Disorders After Cognitive Behavioral Therapy: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Artificial intelligence and patient reported outcomes in ophthalmology.Journal of patient-reported outcomes · 2026Pooled it
- Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.BMC medical education · 2026Trial
- Optimizing diabetes self-care in patients with limited health literacy: a randomized controlled trial (RCT) of SCT-based education with and without an AI-designed photo-novel.BMC health services research · 2026Trial
- Artificial intelligence/machine learning in Alaska Native healthcare systems: symposium perspectives.International journal of circumpolar health · 2026Article
- The role of digital literacy and ethical awareness in nurses' acceptance of Artificial Intelligence: a cross-sectional questionnaire survey.International journal of nursing studies advances · 2026Article
- Factors affecting nurses' acceptance of a digital triage platform in primary health care in Sweden: an extended UTAUT analysis.Scandinavian journal of primary health care · 2026Article
- Using Theory-Based Frameworks to Identify Barriers, Facilitators, Expectations, and Willingness to Pay for Online Medical Consultation Services in China: Qualitative Study.JMIR human factors · 2026Article
- Perspectives of Patients Regarding Artificial Intelligence and Its Application in Healthcare: A Qualitative Study.Journal of clinical nursing · 2026Article
- Understandability and Actionability of Artificial Intelligence-Assisted Lymphedema Education Material in Patients Undergoing Breast Cancer Surgery: Expert Evaluation.Journal of clinical nursing · 2026Observational
- Shared mechanisms of musculoskeletal dysfunction in type 2 diabetes mellitus: Insights into future therapeutic directions (Review).International journal of molecular medicine · 2026Review
1,052 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionHealthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI's role in clinical practice is crucial for successful implementation by equipping healthcare providers with essential knowledge and tools. RESEARCH SIGNIFICANCE: This review article provides a comprehensive and up-to-date overview of the current state of AI in clinical practice, including its potential applications in disease diagnosis, treatment recommendations, and patient engagement. It also discusses the associated challenges, covering ethical and legal considerations and the need for human expertise. By doing so, it enhances understanding of AI's significance in healthcare and supports healthcare organizations in effectively adopting AI technologies. MATERIALS AND
methodsThe current investigation analyzed the use of AI in the healthcare system with a comprehensive review of relevant indexed literature, such as PubMed/Medline, Scopus, and EMBASE, with no time constraints but limited to articles published in English. The focused question explores the impact of applying AI in healthcare settings and the potential outcomes of this application.
resultsIntegrating AI into healthcare holds excellent potential for improving disease diagnosis, treatment selection, and clinical laboratory testing. AI tools can leverage large datasets and identify patterns to surpass human performance in several healthcare aspects. AI offers increased accuracy, reduced costs, and time savings while minimizing human errors. It can revolutionize personalized medicine, optimize medication dosages, enhance population health management, establish guidelines, provide virtual health assistants, support mental health care, improve patient education, and influence patient-physician trust.
conclusionAI can be used to diagnose diseases, develop personalized treatment plans, and assist clinicians with decision-making. Rather than simply automating tasks, AI is about developing technologies that can enhance patient care across healthcare settings. However, challenges related to data privacy, bias, and the need for human expertise must be addressed for the responsible and effective implementation of AI in healthcare.
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.