[This corrects the article
✦ The floor
Discussion
Signed responses from readers of the wire.
✦ Clinical Takeaway ✦
No actionable change — this is an administrative correction to a previously published study; clinicians should consult the corrected version of the original article before drawing conclusions about fNIRS-based tinnitus measurement.
✦ Why It Matters ✦
Corrections to published research on objective tinnitus measurement matter because the field lacks reliable objective biomarkers, and inaccurate data could mislead future research directions.
✦ Key Points ✦
- 01This is a correction notice, not a new study — it amends a previously published PLoS ONE article.
- 02The original study used functional near-infrared spectroscopy (fNIRS) and machine learning to measure tinnitus objectively.
- 03Objective measurement of tinnitus remains an important unmet need in audiology.
- 04Readers should refer to the corrected article (original DOI: 10.1371/journal.pone.0241695) for accurate data.
- 05The nature and extent of the correction are not detailed in the available metadata.
✦ Claims & Evidence ✦
ClaimEvidenceSupport
Functional near-infrared spectroscopy combined with machine learning can objectively measure tinnitus.
studyunclear✦ Research metadata ✦
- PMID
- 42821511
- DOI
- 10.1371/journal.pone.0359852.
- Journal
- PLOS ONE
- Publication type
- editorial
- Evidence level
- 4
- Population
- Participants with tinnitus (from original study)
- Intervention
- Functional near-infrared spectroscopy (fNIRS) combined with machine learning for objective tinnitus measurement
Primary outcomes
Objective measurement of tinnitus using fNIRS and machine learning