Evidence map›Paper›PMID 40502215›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2025

Toward Automated Clinical Transcriptions.

Mitchell A Klusty, W Vaiden Logan, Samuel E Armstrong, Aaron D Mullen, Caroline N Leach, Ken Calvert, Jeff Talbert, V K Cody Bumgardner

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 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. ReflectOR: an LLM-based Agent for Post-Operative Surgical Debriefing.... International Workshop on Spoken Dialogue Systems Technology. International Workshop on Spoken Dialogue Systems Technology · 2026
    Article
  2. Review
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

8 authors.

Mitchell A KlustyUniversity of Kentucky, Lexington, KY, USA.
W Vaiden LoganUniversity of Kentucky, Lexington, KY, USA.
Samuel E ArmstrongUniversity of Kentucky, Lexington, KY, USA.
Aaron D MullenUniversity of Kentucky, Lexington, KY, USA.
Caroline N LeachUniversity of Kentucky, Lexington, KY, USA.
Ken CalvertUniversity of Kentucky, Lexington, KY, USA.
Jeff TalbertUniversity of Kentucky, Lexington, KY, USA.
V K Cody BumgardnerUniversity of Kentucky, Lexington, KY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Administrative documentation is a major driver of rising healthcare costs and is linked to adverse outcomes, including physician burnout and diminished quality of care. This paper introduces a secure system that applies recent advancements in speech-to-text transcription and speaker-labeling (diarization) to patient-provider conversations. This system is optimized to produce accurate transcriptions and highlight potential errors to promote rapid human verification, further reducing the necessary manual effort. Applied to over 40 hours of simulated conversations, this system offers a promising foundation for automating clinical transcriptions.

Identifiers

PMID40502215
PMCPMC12150720

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.