ArticleHealth science reports2025
The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency.
Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 8 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
70 citing papers in PubMed, 8 syntheses or guidelines pooled 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
- A Comprehensive Review of the Revolutionary Potential of Blockchain in Safe, Secure, and Sustainable Pharmaceutical Operations.Pharmaceutical research · 2026Pooled it
- AI applications in lumbar and lumbosacral pedicle screw placement: a systematic review of limited evidence and future directions.Neurosurgical review · 2026Pooled it
- Artificial intelligence-enabled liquid biopsy in cancer: a systematic review and meta- analysis of diagnostic performance and biological implications.Frontiers in oncology · 2026Pooled it
- Artificial intelligence in nursing: a systematic review of attitudes, literacy, readiness, and adoption intentions among nursing students and practicing nurses.Frontiers in digital health · 2025Pooled it
- Large language models in real-world clinical workflows: a systematic review of applications and implementation.Frontiers in digital health · 2025Pooled it
- Recommendations of the Brazilian Society of Nephrology for the management of chronic kidney disease in primary health care.Jornal brasileiro de nefrologiaGuideline
- Artificial Intelligence in Healthcare Practice: Validation, Fairness, and Regulatory Challenges: A Systematic Review.Inquiry : a journal of medical care organization, provision and financingPooled it
- Artificial intelligence/machine learning in Alaska Native healthcare systems: symposium perspectives.International journal of circumpolar health · 2026Article
- Patients' Perspectives on Artificial Intelligence and Digital Transformation in Dental Practice: A Cross-Sectional Study from Romania.Dentistry journal · 2026Article
- Systems Bioengineering of Septic Shock Metabolism: Citrulline, β-Hydroxybutyrate and Plasma Biomarker-Based Phenotyping.Biomolecules · 2026Review
- Comparative Analysis by Machine Learning of Geriatric Frailty and Alzheimer's Disease Classification Using Independent Datasets.Life (Basel, Switzerland) · 2026Article
- AI in Psychiatry for Improving Continuity of Patient Care: Protocol for a Mixed Methods Systematic Review.JMIR research protocols · 2026Article
- The Scale for AI Literacy in Health Care Workers: Development and Validation.Journal of medical Internet research · 2026Article
- Awareness, knowledge and attitudes towards artificial intelligence among nursing students: a systematic review protocol.BMJ open · 2026Article
- Clinical AI Beyond Development: A Scoping Review of Deployment-Related Robustness, Algorithmovigilance, and Lifecycle Oversight.Healthcare (Basel, Switzerland) · 2026Review
- Fixing Work, Not Workers: Leveraging Artificial Intelligence to Combat Burnout in Canadian Healthcare.Healthcare management forum · 2026Article
- Generative AI in healthcare: redefining clinical practice through digital transformation.Health economics review · 2026Article
- AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Review
10 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
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment. Methods: This review analyzes the impact of AI on healthcare using data from the Web of Science (2014-2024), focusing on keywords like AI, ML, and healthcare applications. It examines the uses and effects of AI on healthcare by synthesizing recent literature and real-world case studies, such as Google Health and IBM Watson Health, highlighting AI technologies, their useful applications, and the difficulties in putting them into practice, including problems with data security and resource limitations. The review also discusses new developments in AI, and how they can affect society. Results: The findings demonstrate how AI is enhancing the skills of medical professionals, enhancing diagnosis, and opening the door to more individualized treatment plans, as reflected in the steady rise of AI-related healthcare publications from 158 articles (3.54%) in 2014 to 731 articles (16.33%) by 2024. Core applications like remote monitoring and predictive analytics improve operational effectiveness and patient involvement. However, there are major obstacles to the mainstream implementation of AI in healthcare, including issues with data security and budget constraints. Conclusion: Healthcare may be transformed by AI, but its successful use requires ethical and responsible use. To meet the changing demands of the healthcare sector and guarantee the responsible application of AI technologies, the evaluation highlights the necessity of ongoing research, instruction, and multidisciplinary cooperation. In the future, integrating AI responsibly will be essential to optimizing its advantages and reducing related dangers.
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.