Evidence map›Paper›PMID 40815794›Full record

ArticleJMIR medical education2025

Quo Vadis, AI-Empowered Doctor?

Gary Takahashi, Laurentius von Liechti, Ebrahim Tarshizi

Abstract read
In one paragraph

Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Gary Takahashi *Shiley-Marcos School of Engineering, University of San Diego, 5998 Alcalá Park, San Diego, CA, 92110, United States, 1 503 847 3079.ORCID 0000-0002-1572-5413
Laurentius von Liechti *Shiley-Marcos School of Engineering, University of San Diego, 5998 Alcalá Park, San Diego, CA, 92110, United States, 1 503 847 3079.ORCID 0009-0005-4736-6987
Ebrahim Tarshizi *Shiley-Marcos School of Engineering, University of San Diego, 5998 Alcalá Park, San Diego, CA, 92110, United States, 1 503 847 3079.ORCID 0009-0002-3769-3456

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: In the first decade of this century, physicians maintained considerable professional autonomy, enabling discretionary evaluation and implementation of new technologies according to individual practice requirements. The past decade, however, has witnessed significant restructuring of medical practice patterns in the United States, with most physicians transitioning to employed status. Concurrently, technological advances and other incentives drove the implementation of electronic systems into the clinic, which these physicians were compelled to integrate. Health care practitioners have now been introduced to applications based on large language models, largely driven by artificial intelligence (AI) developers as well as established electronic health record vendors eager to incorporate these innovations. Although generative AI assistance promises enhanced clinical efficiency and diagnostic precision, its rapid advancement may potentially redefine clinical provider roles and transform workflows, as it has already altered expectations of physician productivity, as well as introduced unprecedented liability considerations. Recognition of the input of physicians and other clinical stakeholders in this nascent stage of AI integration is essential. This requires a more comprehensive understanding of AI as a sophisticated clinical tool. Accordingly, we advocate for its systematic incorporation into standard medical curricula.

Indexed as

Artificial IntelligencePhysiciansElectronic Health RecordsHumansUnited StatesAIAI in medicineartificial intelligenceclinical medicinedecision supportlarge language modelsLLM

Identifiers

PMID40815794
PMCPMC12356520

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.