Evidence map›Paper›PMID 39820845›Full record

ArticleJournal of medical systems2025

Generative Artificial Intelligence Use in Healthcare: Opportunities for Clinical Excellence and Administrative Efficiency.

Soumitra S Bhuyan, Vidyoth Sateesh, Naya Mukul, Alay Galvankar, Asos Mahmood, Muhammad Nauman, Akash Rai, Kahuwa Bordoloi, Urmi Basu, Jim Samuel

Registry-linked trialAbstract read
In one paragraph

Article in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07489261 (Effect of Mobile Application- and Artificial Intelligence-Supported Video-Based Patient Education on Patient Outcomes in Teaching Clean Intermittent Catheterization), which is not on this map. Cited by 52 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT07489261 narecruitingnot on this mapstarted 2026, after this paper: background citation

Effect of Mobile Application- and Artificial Intelligence-Supported Video-Based Patient Education on Patient Outcomes in Teaching Clean Intermittent Catheterization

TypeinterventionalSponsorMersin UniversityRan2026 to 2027Enrolled99ConditionsClean Intermittent CatheterizationArmsMobile application, Artifial intellgience
3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. [Medical education and artificial intelligence: perspectives and ethical challenges].Revista medica del Instituto Mexicano del Seguro Social · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Soumitra S BhuyanEdward J. Bloustein School of Planning and Public Policy, Rutgers, The State University of New Jersey, 255, Civic Square Building 33 Livingston Ave #400, New Brunswick, NJ, 08901, USA. Soumitra.bhuyan@rutgers.edu.
Vidyoth SateeshEdward J. Bloustein School of Planning and Public Policy, Rutgers, The State University of New Jersey, 255, Civic Square Building 33 Livingston Ave #400, New Brunswick, NJ, 08901, USA.
Naya MukulSchool of Social Policy, Rice University, Houston, TX, USA.
Alay GalvankarBiotechnology High School, Freehold, NJ, USA.
Asos MahmoodCenter for Health System Improvement, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA.
Muhammad NaumanUniversity of Engineering & Technology, Peshawar, Pakistan.
Akash RaiEdward J. Bloustein School of Planning and Public Policy, Rutgers, The State University of New Jersey, 255, Civic Square Building 33 Livingston Ave #400, New Brunswick, NJ, 08901, USA.
Kahuwa BordoloiDepartment of Psychology and Counselling, St. Joseph's University, Bangalore, India.
Urmi BasuInsight Biopharma, Princeton, NJ, USA.
Jim SamuelEdward J. Bloustein School of Planning and Public Policy, Rutgers, The State University of New Jersey, 255, Civic Square Building 33 Livingston Ave #400, New Brunswick, NJ, 08901, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generative Artificial Intelligence (Gen AI) has transformative potential in healthcare to enhance patient care, personalize treatment options, train healthcare professionals, and advance medical research. This paper examines various clinical and non-clinical applications of Gen AI. In clinical settings, Gen AI supports the creation of customized treatment plans, generation of synthetic data, analysis of medical images, nursing workflow management, risk prediction, pandemic preparedness, and population health management. By automating administrative tasks such as medical documentations, Gen AI has the potential to reduce clinician burnout, freeing more time for direct patient care. Furthermore, application of Gen AI may enhance surgical outcomes by providing real-time feedback and automation of certain tasks in operating rooms. The generation of synthetic data opens new avenues for model training for diseases and simulation, enhancing research capabilities and improving predictive accuracy. In non-clinical contexts, Gen AI improves medical education, public relations, revenue cycle management, healthcare marketing etc. Its capacity for continuous learning and adaptation enables it to drive ongoing improvements in clinical and operational efficiencies, making healthcare delivery more proactive, predictive, and precise.

Indexed as

Artificial IntelligenceDelivery of Health CareEfficiency, OrganizationalGenerative Artificial IntelligenceHumansWorkflowAI applicationsArtificial intelligenceChatGPTClinical excellenceEthicsGenerative AIHealthcareHealth information technologyLarge language modelsMedicine

Identifiers

PMID39820845
PMCPMC11739231

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.