Evidence map›Paper›PMID 38610682›Full record

ArticleJournal of clinical medicine2024

A Mixed-Rate Strategy on a Bilaterally-Synchronized Cochlear Implant Processor Offering the Opportunity to Provide Both Speech Understanding and Interaural Time Difference Cues.

Stephen R Dennison, Tanvi Thakkar, Alan Kan, Mario A Svirsky, Mahan Azadpour, Ruth Y Litovsky

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. A deep learning framework for understanding cochlear implants.bioRxiv : the preprint server for biology · 2025
    Article
  3. 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

6 authors.

Stephen R DennisonWaisman Center, University of Wisconsin-Madison, Madison, WI 53706, USA.
Tanvi ThakkarDepartment of Psychology, University of Wisconsin-La Crosse, La Crosse, WI 54601, USA.
Alan KanSchool of Engineering, Macquarie University, Sydney, NSW 2109, Australia.ORCID 0000-0001-6033-0958
Mario A SvirskyDepartment of Otolaryngology, New York University, New York, NY 10016, USA.ORCID 0000-0002-9238-0682
Mahan AzadpourDepartment of Otolaryngology, New York University, New York, NY 10016, USA.
Ruth Y LitovskyWaisman Center, University of Wisconsin-Madison, Madison, WI 53706, USA.

Funding

Directional Hearing in Complex Auditory EnvironmentsR01DC003083 · NIDCD · UNIVERSITY OF WISCONSIN-MADISON · PI LITOVSKY, RUTH Y · 2004 to 2020
$7.4M
Waisman Intellectual and Developmental Disabilities Research Center Down Syndrome RegistryU54HD090256 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI CHANG, QIANG · 2016 to 2020
$6.0M
CCI-Mobile: Signal Processing Advancements for Cochlear Implant Users in Naturalistic EnvironmentsR01DC016839 · NIDCD · UNIVERSITY OF TEXAS DALLAS · PI HANSEN, JOHN H.L., LITOVSKY, RUTH Y · 2018 to 2022
$3.6M
User customization and user optimization of cochlear implant devicesR01DC010494 · NIDCD · UNIVERSITY OF TEXAS DALLAS · PI HANSEN, JOHN H.L. · 2010 to 2015
$3.1M
Binaural processing and hearing in children with cochlear implantsR01DC020355 · NIDCD · UNIVERSITY OF WISCONSIN-MADISON · PI Ruth Y Litovsky · 2023 to 2026
$2.3M
NICHD NIH HHS U54 HD090256NIDCD NIH HHS R01 DC003083NIDCD NIH HHS R01 DC010494NIDCD NIH HHS R01 DC016839NIDCD NIH HHS R01DC016839NIDCD NIH HHS R01 DC020355NIDCD NIH HHS R01DC03083
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

binaural hearingcochlear implantsresearch processorsynchronization

Identifiers

PMID38610682
PMCPMC11012985

What OpenQuestion 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 OpenQuestion graph.