Evidence map›Paper›PMID 38839555›Full record

ReviewOtolaryngologic clinics of North America2024

Artificial Intelligence in Otolaryngology: Topics in Epistemology & Ethics.

Katie Tai, Robin Zhao, Anaïs Rameau

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Otolaryngologic clinics of North America, 2024. 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

3 authors.

Katie TaiNew York Presbyterian Hospital, 1300 York Avenue, New York, NY 10065, USA.
Robin ZhaoDepartment of Otolaryngology-Head & Neck Surgery, Sean Parker Institute for the Voice, Weill Cornell Medical College, 240 East 59th Street, New York, NY 10022, USA.
Anaïs RameauDepartment of Otolaryngology-Head & Neck Surgery, Sean Parker Institute for the Voice, Weill Cornell Medical College, 240 East 59th Street, New York, NY 10022, USA. Electronic address: anr2783@med.cornell.edu.

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
Developing an App-Based Voice Clinical Decision Support Tool to Augment the Sensitivity of the Bedside Swallow Evaluation in Older AdultsK76AG079040 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Anais Rameau · 2022 to 2026
$972k
NIA NIH HHS K76 AG079040NIH HHS OT2 OD032720
6 · The paper itself

Abstract

To fuel artificial intelligence (AI) potential in clinical practice in otolaryngology, researchers must understand its epistemic limitations, which are tightly linked to ethical dilemmas requiring careful consideration. AI tools are fundamentally opaque systems, though there are methods to increase explainability and transparency. Reproducibility and replicability limitations can be overcomed by sharing computing code, raw data, and data processing methodology. The risk of bias can be mitigated via algorithmic auditing, careful consideration of the training data, and advocating for a diverse AI workforce to promote algorithmic pluralism, reflecting our population's diverse values and preferences.

Indexed as

Artificial IntelligenceOtolaryngologyHumansKnowledgeReproducibility of ResultsArtificial intelligence epistemologyArtificial intelligence ethicsArtificial intelligence governanceBiasExplainability

Identifiers

PMID38839555
PMCPMC11374503

What OpenQuestion holds

Textmetadata
LicenceTDM
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.