Evidence map›Paper›PMID 42639494›Full record

ArticleLaryngoscope investigative otolaryngology2026

Large Language Models for Optimizing Patient Recruitment Decisions in Voice Data Generation Projects.

James Anibal, Geetha Krishna Chaitanya Nama, Shrramana Ganesh, Yosef Nafii, Samantha Salvi Cruz, Veronica Daoud, Madeleine Zanin, Tram Le, Parsa Khorrami, Bradford J Wood and 53 more

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Article in Laryngoscope investigative otolaryngology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

63 authors.

James AnibalComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.ORCID https://orcid.org/0009-0009-1196-2153
Geetha Krishna Chaitanya NamaDepartment of Computer Science and Engineering University of South Florida Tampa Florida USA.
Shrramana GaneshUSF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa Florida USA.
Yosef NafiiUSF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa Florida USA.ORCID https://orcid.org/0009-0006-3600-6705
Samantha Salvi CruzVanderbilt University Medical Center Nashville Tennessee USA.ORCID https://orcid.org/0009-0000-6083-657X
Veronica DaoudUSF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa Florida USA.ORCID https://orcid.org/0009-0001-2160-5071
Madeleine ZaninMount Sinai Hospital Toronto Ontario Canada.
Tram LeUSF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa Florida USA.
Parsa KhorramiDepartment of Computer Science and Engineering University of South Florida Tampa Florida USA.ORCID https://orcid.org/0009-0006-4747-4192
Bradford J WoodCenter for Interventional Oncology NIH Clinical Center, National Institutes of Health Bethesda Maryland USA.
David CliftonComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Jamie ToghranegarUSF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa Florida USA.
Yael BensoussanUSF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa Florida USA.ORCID https://orcid.org/0000-0002-1635-8627
Yael E BensoussanComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Olivier ElementoComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Jean-Christophe Bélisle-PiponComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
David DorrComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Satrajit GhoshComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Alistair JohnsonComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Phillip PayneComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Maria E PowellComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Anaïs RameauComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Vardit RavitskyComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Alexandros SigarasComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Shaheen AwanComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Ruth BahrComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Donald BolserComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Kathy J JenkinsComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Frank RudziczComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Jennifer SiuComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Stephanie WattsComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Yassmeen Abdel-AtyComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Toufeeq Ahmed SyedComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
James AnibalComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Steven BedrickComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Isaac BeversComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Micah BoyerComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Rahul BritoComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Selina A CasalinoComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
John CostelloComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Enrique Diaz-OcampoComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Mahmoud ElmahdyComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Kenneth FletcherComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Alexander GelbardComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Karim HannaComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Bill HershComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Lochana JayachandranComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Kaley JenneyComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Andrea KrusselComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Chloe LoewithComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Tempestt NealComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Claire Premi-BortolottoComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Sarah RohdeComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Samantha Salvi CruzComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Elizabeth SilberholzComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Duncan SutherlandComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Venkata Swarna Mukhi TalluriComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Jamie ToghranegarComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Kimberly VinsonComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Claire WilsonComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Madeleine ZaninComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Theresa ZesiewiczComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.
Robin ZhaoComputational Health Informatics Lab, Institute of Biomedical Engineering University of Oxford Oxford UK.

Funding

Bridge2AI: Voice as a Biomarker of Health - Building an ethically sourced, bioaccoustic database to understand disease like never beforeOT2OD032720 · OD · UNIVERSITY OF SOUTH FLORIDA · PI BENSOUSSAN, YAEL EMILIE, BÉLISLE-PIPON, JEAN-CHRISTOPHE · 2022 to 2025
$18.0M
NIH HHS OT2 OD032720
6 · The paper itself

Abstract

Objectives: Past studies have shown that many clinical machine learning models have performance limitations due to imbalances in the training data. For voice data generation projects, the origin of the problem may lie in the recruiting methods used during data collection efforts. This study introduces a generative AI pipeline for "dataset decision support", recommending recruitment decisions based on high-dimensional insights. Methods: The publicly available GOSSIS-1-eICU dataset was filtered to create patient populations that were relevant to voice data generation projects. Lab results and vital signs from the electronic health record were also used to train a neural network for prediction of disease type. Prediction uncertainty estimates were included in the dataset as approximate indicators of health complexity. To select the best recruitment choice for addressing imbalances, an open-source large language model (LLM) was then instructed to assess dataset statistics and the characteristics of possible participants. Simulations were run in which the system constructed datasets of 250 patients. Results: In over 90% of cases, the proposed system reduced categorical imbalances and widened continuous distributions when compared to randomly sampled counterfactual datasets ( Conclusion: LLMs may provide useful, explainable recommendations when presented with dataset distribution statistics and candidate profiles. In the future, this simulated scenario may be extended to align with conditions in emergency departments or other high-volume settings. Level of Evidence: 3.

Indexed as

artificial intelligencebias mitigationdataset optimizationlarge language models

Identifiers

PMID42639494
PMCPMC13502059

What OpenQuestion holds

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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.