ArticleEar and hearing
Computational Audiology: New Approaches to Advance Hearing Health Care in the Digital Age.
Article in Ear and hearing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ototoxicity prognostic models in adult and pediatric cancer patients: a rapid review.Journal of cancer survivorship : research and practice · 2023Pooled it
- Factors Influencing Hearing Help-Seeking and Hearing Aid Uptake in Adults: A Systematic Review of the Past Decade.Trends in hearingPooled it
- Evaluating the Impact of Hearing Conditioning App on Clinician Task Load and Hearing Test Efficiency in Children.The journal of international advanced otology · 2025Trial
- Artificial intelligence and hearing health: a global evidence review of biases and equity implications for Africa.Global health action · 2026Review
- Article
- Perspectives of audiologists in China on artificial intelligence in clinical practice and professional identity: a qualitative study.BMC medical education · 2026Article
- Patient Perceptions of Delays in Audiology Services in Johannesburg: A Secondary Analysis of Waiting Times and Alternative Service Models.Journal of evaluation in clinical practice · 2026Article
- Leveraging spatial cues from cochlear implant microphones to efficiently enhance speech separation in naturalistic listening scenes.Scientific reports · 2025Article
- Neuropsychological Assessments to Explore the Cognitive Impact of Cochlear Implants: A Scoping Review.Journal of clinical medicine · 2025Review
- Remote self-report and speech-in-noise measures predict clinical audiometric thresholds.International journal of audiology · 2025Article
- Use of artificial intelligence tools by audiologists and speech-language therapists: an international survey of academicians.Journal of otology · 2025Article
- Electrical Bioimpedance-Based Monitoring of Intracochlear Tissue Changes After Cochlear Implantation.Sensors (Basel, Switzerland) · 2024Article
- Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.Sensors (Basel, Switzerland) · 2024Article
- Review
- Automated hearing loss type classification based on pure tone audiometry data.Scientific reports · 2024Article
- Exploring the Performance of ChatGPT-4 in the Taiwan Audiologist Qualification Examination: Preliminary Observational Study Highlighting the Potential of AI Chatbots in Hearing Care.JMIR medical education · 2024Observational
- Active transfer learning for audiogram estimation.Frontiers in digital health · 2024Article
- Digital Transformation in Healthcare: Technology Acceptance and Its Applications.International journal of environmental research and public health · 2023Article
- Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.Journal of the Association for Research in Otolaryngology : JARO · 2022Review
- Digital Approaches to Automated and Machine Learning Assessments of Hearing: Scoping Review.Journal of medical Internet research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The global digital transformation enables computational audiology for advanced clinical applications that can reduce the global burden of hearing loss. In this article, we describe emerging hearing-related artificial intelligence applications and argue for their potential to improve access, precision, and efficiency of hearing health care services. Also, we raise awareness of risks that must be addressed to enable a safe digital transformation in audiology. We envision a future where computational audiology is implemented via interoperable systems using shared data and where health care providers adopt expanded roles within a network of distributed expertise. This effort should take place in a health care system where privacy, responsibility of each stakeholder, and patients' safety and autonomy are all guarded by design.
Indexed as
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What OpenQuestion holds
Registered trials
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.