Evidence map›Paper›PMID 41832341›Full record

ArticleNPJ digital medicine2026

The role of agentic artificial intelligence in healthcare: a scoping review.

Bernardo G Collaco, Syed Ali Haider, Srinivasagam Prabha, Cesar A Gomez-Cabello, Ariana Genovese, Nadia G Wood, Sanjay P Bagaria, Narayanan Gopala, Cui Tao, Antonio Jorge Forte

Abstract read
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Trial
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  4. AI agents in cancer imaging: Concepts, advances, and clinical perspectives.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026
    Article
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  9. Review
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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.

Bernardo G CollacoDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
Syed Ali HaiderDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
Srinivasagam PrabhaDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
Cesar A Gomez-CabelloDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
Ariana GenoveseDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA.
Nadia G WoodDepartment of Radiology AI IT, Mayo Clinic, Rochester, MN, USA.
Sanjay P BagariaDepartment of Surgery, Mayo Clinic, Jacksonville, FL, USA.
Narayanan GopalaCenter for Digital Health, Mayo Clinic, Rochester, MN, USA.
Cui TaoDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Jacksonville, FL, USA.
Antonio Jorge ForteDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA. ajvforte@yahoo.com.br.ORCID http://orcid.org/0000-0003-2004-7538

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Agentic AI represents a promising evolution of artificial intelligence in healthcare, with systems capable of operating autonomously to achieve defined clinical goals. However, the literature lacks conceptual clarity in distinguishing AI agents from Agentic AI, and few studies have rigorously explored their applications. We conducted a scoping review across five databases, identifying seven eligible studies spanning emergency medicine, oncology, radiology, and rehabilitation. The included systems demonstrated features such as autonomous operation, goal-directed behavior, action initiation, and, in some cases, multi-agent collaboration. Reported outcomes included high accuracy in cancer diagnosis, treatment planning, alert generation, coaching, and workflow optimization. Despite promising results, most studies were exploratory, limited in scope, and lacked robust clinical validation, with only one trial involving patients. These findings highlight both the potential and immaturity of Agentic AI in healthcare, underscoring the need for standardized definitions, regulatory guidance, and rigorous evaluation to ensure safe and effective integration into practice.

Identifiers

PMID41832341
PMCPMC13133135

What OpenQuestion holds

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Registered trials

None linked

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.