SynthesisCurrent topics in medicinal chemistry2025
The Impact and Role of Artificial Intelligence (AI) in Healthcare: Systematic Review.
Synthesis in Current topics in medicinal chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- "First, do no harm" in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence: A systematic literature review.BMC medical ethics · 2026Pooled it
- Shaping the Future of Men's Health: How AI Could Be a Transformative Tool for Better Patient Outcomes and Provider Efficiency.Journal of medical Internet research · 2026Article
- Work autonomy mediates associations between medical AI readiness and well being in a three wave nurse study.Scientific reports · 2026Article
- AI in respiratory care: findings from the GOLD report.Journal of translational medicine · 2026Article
- Beyond translation: a patient-centered research agenda for artificial intelligence interpreter services in healthcare.NPJ digital medicine · 2026Article
- Clinical Artificial Intelligence Agents in Nephrology: From Prediction to Action Through Workflow-Native Intelligence-A Roadmap for Workflow-Integrated Care.Journal of clinical medicine · 2026Review
- Overcoming domain-specific challenges for artificial intelligence in abdominal oncology toward clinical translation.Discover oncology · 2026Review
- Artificial intelligence-assisted medical coding and DRG management: current applications, challenges, and future perspectives.Frontiers in medicine · 2026Review
- Artificial intelligence use as a key predictor of clinical performance in nursing students: a cross-sectional study from Iran.BMC medical education · 2025Article
- ETHICS of AI Adoption and Deployment in Health Care: Progress, Challenges, and Next Steps.JMIR AI · 2025Article
- Challenges of using artificial intelligence in Iran's health system: a qualitative study.Journal of preventive medicine and hygiene · 2025Article
- Evaluation of deepseek, gemini, ChatGPT-4o, and perplexity in responding to salivary gland cancer.BMC oral health · 2025Article
- Barriers and Facilitators to Artificial Intelligence Implementation in Diabetes Management from Healthcare Workers' Perspective: A Scoping Review.Medicina (Kaunas, Lithuania) · 2025Article
- A NLP analysis of digital demand for healthcare jobs in China.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionHealthcare organizations are complicated and demanding for all stakeholders, but artificial intelligence (AI) has revolutionized several sectors, especially healthcare, with the potential to enhance patient outcomes and standard of life. Quick advancements in AI can transform healthcare by implementing it into clinical procedures. Reporting AI's involvement in clinical settings is vital for its successful adoption by providing medical professionals with the necessary information and tools.
backgroundThis paper offers a thorough and up-to-date summary of the present condition of AI in medical settings, including its possible uses in patient interaction, treatment suggestions, and disease diagnosis. It also addresses the challenges and limitations, including the necessity for human expertise along with future directions. In doing so, it improves the understanding of AI's relevance in healthcare and supports medical institutions in successfully implementing AI technologies.
methodsThe structured literature review, with its dependable and reproducible research process, allowed the authors to acquire 337 peer-reviewed publications from indexing databases, such as Scopus and EMBASE, without any time restrictions. The researchers utilized both qualitative and quantitative factors to assess authors, publications, keywords, and collaboration networks.
resultsAI implementation in healthcare holds enormous potential for enhancing patient outcomes, treatment recommendations, and disease diagnosis. AI technologies can use massive datasets and recognize patterns to beat human performance in various healthcare domains. AI provides improved accuracy, reduced expenses, and time savings. It can transform customized medicine, optimize drug dosages, improve management of population health, set guidelines, offer digital medical assistants, promote mental health services, boost patient knowledge, and maintain patientclinician trust.
conclusionAI can be utilized to detect diseases, develop customized therapy plans, and support medical professionals with their clinical decision-making. Instead of just automating jobs, AI focuses on creating technologies that can improve patient care in several healthcare settings. However, challenges such as biasness, data confidentiality, and data quality must be resolved for the appropriate and successful integration of AI in healthcare.
Indexed as
Identifiers
40033599What Socratic 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 Socratic graph.